1
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Della Rosa G, Gostynska N, Ephraim JW, Marras S, Moroni M, Tirelli N, Panuccio G, Palazzolo G. Magnesium vs. sodium alginate as precursors of calcium alginate: Mechanical differences and advantages in the development of functional neuronal networks. Carbohydr Polym 2024; 342:122375. [PMID: 39048194 DOI: 10.1016/j.carbpol.2024.122375] [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: 02/27/2024] [Revised: 06/04/2024] [Accepted: 06/05/2024] [Indexed: 07/27/2024]
Abstract
Calcium alginate is one of the most widely employed matrices in regenerative medicine. A downside is its heterogeneity, due to the poorly controllable character of the gelation of sodium alginate (NaAlg), i.e. the commonly used alginate salt, with calcium. Here, we have used magnesium alginate (MgAlg) as an alternative precursor of calcium alginate. MgAlg coils, more compact and thus less entangled than those of NaAlg, allow for an easier diffusion of calcium ions, whereas Mg is exchanged with calcium more slowly than Na; this allows for the formation of a material (Ca(Mg)Alg) with a more reversible creep behaviour than Ca(Na)Alg, due to a more homogeneous - albeit lower - density of elastically active cross-links. We also show that Ca(Mg)Alg supports better than Ca(Na)Alg the network development and function of embedded (rat cortical) neurons: they show greater neurite extension and branching at 7 and 21 days (Tubb3 and Map2 immunofluorescence) and better neuronal network functional maturation / more robust and longer-lasting activity, probed by calcium imaging and microelectrode array electrophysiology. Overall, our results unveil the potential of MgAlg as bioactive biomaterial for enabling the formation of functional neuron-based tissue analogues.
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Affiliation(s)
- Giulia Della Rosa
- Istituto Italiano di Tecnologia, Laboratory for Enhanced Regenerative Medicine, Genova, Italy; University of Pavia, Department of Molecular Medicine, Pavia, Italy.
| | - Natalia Gostynska
- Istituto Italiano di Tecnologia, Laboratory for Enhanced Regenerative Medicine, Genova, Italy.
| | - John W Ephraim
- Istituto Italiano di Tecnologia, Laboratory for Enhanced Regenerative Medicine, Genova, Italy.
| | - Sergio Marras
- Istituto Italiano di Tecnologia, Materials Characterization Facility, Genova, Italy.
| | | | - Nicola Tirelli
- Istituto Italiano di Tecnologia, Laboratory for Polymers and Biomaterials, Genova, Italy.
| | - Gabriella Panuccio
- Istituto Italiano di Tecnologia, Laboratory for Enhanced Regenerative Medicine, Genova, Italy.
| | - Gemma Palazzolo
- Istituto Italiano di Tecnologia, Laboratory for Enhanced Regenerative Medicine, Genova, Italy.
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2
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Sihn D, Chae S, Kim SP. A method to find temporal structure of neuronal coactivity patterns with across-trial correlations. J Neurosci Methods 2024; 408:110172. [PMID: 38782124 DOI: 10.1016/j.jneumeth.2024.110172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Revised: 05/08/2024] [Accepted: 05/17/2024] [Indexed: 05/25/2024]
Abstract
BACKGROUND The across-trial correlation of neurons' coactivity patterns emerges to be important for information coding, but methods for finding their temporal structures remain largely unexplored. NEW METHOD In the present study, we propose a method to find time clusters in which coactivity patterns of neurons are correlated across trials. We transform the multidimensional neural activity at each timing into a coactivity pattern of binary states, and predict the coactivity patterns at different timings. We devise a method suitable for these coactivity pattern predictions, call general event prediction. Cross-temporal prediction accuracy is then used to estimate across-trial correlations between coactivity patterns at two timings. We extract time clusters from the cross-temporal prediction accuracy by a modified k-means algorithm. RESULTS The feasibility of the proposed method is verified through simulations based on ground truth. We apply the proposed method to a calcium imaging dataset recorded from the motor cortex of mice, and demonstrate time clusters of motor cortical coactivity patterns during a motor task. COMPARISON WITH EXISTING METHODS While the existing cosine similarity method, which does not account for across-trial correlation, shows temporal structures only for contralateral neural responses, the proposed method reveals those for both contralateral and ipsilateral neural responses, demonstrating the effect of across-trial correlations. CONCLUSIONS This study introduces a novel method for measuring the temporal structure of neuronal ensemble activity.
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Affiliation(s)
- Duho Sihn
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan 44919, the Republic of Korea
| | - Soyoung Chae
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan 44919, the Republic of Korea
| | - Sung-Phil Kim
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan 44919, the Republic of Korea.
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3
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Lin H, Zhou J. Hippocampal and orbitofrontal neurons contribute to complementary aspects of associative structure. Nat Commun 2024; 15:5283. [PMID: 38902232 PMCID: PMC11190210 DOI: 10.1038/s41467-024-49652-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Accepted: 06/12/2024] [Indexed: 06/22/2024] Open
Abstract
The ability to establish associations between environmental stimuli is fundamental for higher-order brain functions like state inference and generalization. Both the hippocampus and orbitofrontal cortex (OFC) play pivotal roles in this, demonstrating complex neural activity changes after associative learning. However, how precisely they contribute to representing learned associations remains unclear. Here, we train head-restrained mice to learn four 'odor-outcome' sequence pairs composed of several task variables-the past and current odor cues, sequence structure of 'cue-outcome' arrangement, and the expected outcome; and perform calcium imaging from these mice throughout learning. Sequence-splitting signals that distinguish between paired sequences are detected in both brain regions, reflecting associative memory formation. Critically, we uncover differential contents in represented associations by examining, in each area, how these task variables affect splitting signal generalization between sequence pairs. Specifically, the hippocampal splitting signals are influenced by the combination of past and current cues that define a particular sensory experience. In contrast, the OFC splitting signals are similar between sequence pairs that share the same sequence structure and expected outcome. These findings suggest that the hippocampus and OFC uniquely and complementarily organize the acquired associative structure.
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Affiliation(s)
- Huixin Lin
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China
- Chinese Institute for Brain Research, Beijing, 102206, China
| | - Jingfeng Zhou
- Chinese Institute for Brain Research, Beijing, 102206, China.
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4
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Sakamoto M, Yokoyama T. Probing neuronal activity with genetically encoded calcium and voltage fluorescent indicators. Neurosci Res 2024:S0168-0102(24)00076-2. [PMID: 38885881 DOI: 10.1016/j.neures.2024.06.004] [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: 02/06/2024] [Revised: 04/09/2024] [Accepted: 06/08/2024] [Indexed: 06/20/2024]
Abstract
Monitoring neural activity in individual neurons is crucial for understanding neural circuits and brain functions. The emergence of optical imaging technologies has dramatically transformed the field of neuroscience, enabling detailed observation of large-scale neuronal populations with both cellular and subcellular resolution. This transformation will be further accelerated by the integration of these imaging technologies and advanced big data analysis. Genetically encoded fluorescent indicators to detect neural activity with high signal-to-noise ratios are pivotal in this advancement. In recent years, these indicators have undergone significant developments, greatly enhancing the understanding of neural dynamics and networks. This review highlights the recent progress in genetically encoded calcium and voltage indicators and discusses the future direction of imaging techniques with big data analysis that deepens our understanding of the complexities of the brain.
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Affiliation(s)
- Masayuki Sakamoto
- Graduate School of Biostudies, Kyoto University, 53 Shogoin Kawara-cho, Sakyo-ku, Kyoto 606-8507, Japan.
| | - Tatsushi Yokoyama
- Graduate School of Biostudies, Kyoto University, 53 Shogoin Kawara-cho, Sakyo-ku, Kyoto 606-8507, Japan
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5
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Sandoval SO, Cappuccio G, Kruth K, Osenberg S, Khalil SM, Méndez-Albelo NM, Padmanabhan K, Wang D, Niciu MJ, Bhattacharyya A, Stein JL, Sousa AMM, Waxman EA, Buttermore ED, Whye D, Sirois CL, Williams A, Maletic-Savatic M, Zhao X. Rigor and reproducibility in human brain organoid research: Where we are and where we need to go. Stem Cell Reports 2024; 19:796-816. [PMID: 38759644 PMCID: PMC11297560 DOI: 10.1016/j.stemcr.2024.04.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Revised: 04/15/2024] [Accepted: 04/16/2024] [Indexed: 05/19/2024] Open
Abstract
Human brain organoid models have emerged as a promising tool for studying human brain development and function. These models preserve human genetics and recapitulate some aspects of human brain development, while facilitating manipulation in an in vitro setting. Despite their potential to transform biology and medicine, concerns persist about their fidelity. To fully harness their potential, it is imperative to establish reliable analytic methods, ensuring rigor and reproducibility. Here, we review current analytical platforms used to characterize human forebrain cortical organoids, highlight challenges, and propose recommendations for future studies to achieve greater precision and uniformity across laboratories.
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Affiliation(s)
- Soraya O Sandoval
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA; Department of Neuroscience, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, USA; Neuroscience Training Program, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Gerarda Cappuccio
- Department of Pediatrics-Neurology, Baylor College of Medicine, Houston, TX, USA; Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX, USA
| | - Karina Kruth
- Department of Psychiatry, University of Iowa Health Care, Iowa City, IA 52242, USA; Iowa Neuroscience Institute, University of Iowa Health Care, Iowa City, IA 52242, USA
| | - Sivan Osenberg
- Department of Pediatrics-Neurology, Baylor College of Medicine, Houston, TX, USA; Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX, USA
| | - Saleh M Khalil
- Department of Pediatrics-Neurology, Baylor College of Medicine, Houston, TX, USA; Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX, USA
| | - Natasha M Méndez-Albelo
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA; Department of Neuroscience, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, USA; Molecular Cellular Pharmacology Training Program, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Krishnan Padmanabhan
- Department of Neuroscience, Center for Visual Science, Del Monte Institute for Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester NY 14642, USA
| | - Daifeng Wang
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA; Departments of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Mark J Niciu
- Department of Psychiatry, University of Iowa Health Care, Iowa City, IA 52242, USA; Iowa Neuroscience Institute, University of Iowa Health Care, Iowa City, IA 52242, USA
| | - Anita Bhattacharyya
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA; Department of Cell and Regenerative Biology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Jason L Stein
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - André M M Sousa
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA; Department of Neuroscience, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Elisa A Waxman
- Center for Cellular and Molecular Therapeutics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA; Center for Epilepsy and NeuroDevelopmental Disorders (ENDD), The Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Elizabeth D Buttermore
- Human Neuron Core, Rosamund Stone Zander Translational Neuroscience Center, Boston Children's Hospital, Boston, MA, USA; F.M. Kirby Neurobiology Department, Boston Children's Hospital, Boston, MA, USA
| | - Dosh Whye
- Human Neuron Core, Rosamund Stone Zander Translational Neuroscience Center, Boston Children's Hospital, Boston, MA, USA; F.M. Kirby Neurobiology Department, Boston Children's Hospital, Boston, MA, USA
| | - Carissa L Sirois
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA; Department of Neuroscience, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Aislinn Williams
- Department of Psychiatry, University of Iowa Health Care, Iowa City, IA 52242, USA; Iowa Neuroscience Institute, University of Iowa Health Care, Iowa City, IA 52242, USA.
| | - Mirjana Maletic-Savatic
- Department of Pediatrics-Neurology, Baylor College of Medicine, Houston, TX, USA; Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX, USA; Center for Drug Discovery, Baylor College of Medicine, Houston, TX, USA; Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA.
| | - Xinyu Zhao
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA; Department of Neuroscience, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, USA.
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6
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Bardella G, Franchini S, Pan L, Balzan R, Ramawat S, Brunamonti E, Pani P, Ferraina S. Neural Activity in Quarks Language: Lattice Field Theory for a Network of Real Neurons. ENTROPY (BASEL, SWITZERLAND) 2024; 26:495. [PMID: 38920504 PMCID: PMC11203154 DOI: 10.3390/e26060495] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/25/2024] [Revised: 05/28/2024] [Accepted: 05/30/2024] [Indexed: 06/27/2024]
Abstract
Brain-computer interfaces have seen extraordinary surges in developments in recent years, and a significant discrepancy now exists between the abundance of available data and the limited headway made in achieving a unified theoretical framework. This discrepancy becomes particularly pronounced when examining the collective neural activity at the micro and meso scale, where a coherent formalization that adequately describes neural interactions is still lacking. Here, we introduce a mathematical framework to analyze systems of natural neurons and interpret the related empirical observations in terms of lattice field theory, an established paradigm from theoretical particle physics and statistical mechanics. Our methods are tailored to interpret data from chronic neural interfaces, especially spike rasters from measurements of single neuron activity, and generalize the maximum entropy model for neural networks so that the time evolution of the system is also taken into account. This is obtained by bridging particle physics and neuroscience, paving the way for particle physics-inspired models of the neocortex.
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Affiliation(s)
- Giampiero Bardella
- Department of Physiology and Pharmacology, Sapienza University of Rome, Piazzale Aldo Moro 5, 00185 Roma, Italy (E.B.); (P.P.); (S.F.)
| | - Simone Franchini
- Department of Physiology and Pharmacology, Sapienza University of Rome, Piazzale Aldo Moro 5, 00185 Roma, Italy (E.B.); (P.P.); (S.F.)
| | - Liming Pan
- School of Cyber Science and Technology, University of Science and Technology of China, Hefei 230026, China;
| | - Riccardo Balzan
- Laboratoire de Chimie et Biochimie Pharmacologiques et Toxicologiques, UMR 8601, UFR Biomédicale et des Sciences de Base, Université Paris Descartes-CNRS, PRES Paris Sorbonne Cité, 75006 Paris, France;
| | - Surabhi Ramawat
- Department of Physiology and Pharmacology, Sapienza University of Rome, Piazzale Aldo Moro 5, 00185 Roma, Italy (E.B.); (P.P.); (S.F.)
| | - Emiliano Brunamonti
- Department of Physiology and Pharmacology, Sapienza University of Rome, Piazzale Aldo Moro 5, 00185 Roma, Italy (E.B.); (P.P.); (S.F.)
| | - Pierpaolo Pani
- Department of Physiology and Pharmacology, Sapienza University of Rome, Piazzale Aldo Moro 5, 00185 Roma, Italy (E.B.); (P.P.); (S.F.)
| | - Stefano Ferraina
- Department of Physiology and Pharmacology, Sapienza University of Rome, Piazzale Aldo Moro 5, 00185 Roma, Italy (E.B.); (P.P.); (S.F.)
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7
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Calcini N, Silva Lantyer AD, Zeldenrust F, Celikel T. Nonlinear super-resolution signal processing allows intracellular tracking of calcium dynamics. J Neural Eng 2024; 21:036008. [PMID: 38648784 DOI: 10.1088/1741-2552/ad417c] [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: 10/22/2023] [Accepted: 04/22/2024] [Indexed: 04/25/2024]
Abstract
Objective.Traditional quantification of fluorescence signals, such asΔF/F, relies on ratiometric measures that necessitate a baseline for comparison, limiting their applicability in dynamic analyses. Our goal here is to develop a baseline-independent method for analyzing fluorescence data that fully exploits temporal dynamics to introduce a novel approach for dynamical super-resolution analysis, including in subcellular resolution.Approach.We introduce ARES (Autoregressive RESiduals), a novel method that leverages the temporal aspect of fluorescence signals. By focusing on the quantification of residuals following linear autoregression, ARES obviates the need for a predefined baseline, enabling a more nuanced analysis of signal dynamics.Main result.We delineate the foundational attributes of ARES, illustrating its capability to enhance both spatial and temporal resolution of calcium fluorescence activity beyond the conventional ratiometric measure (ΔF/F). Additionally, we demonstrate ARES's utility in elucidating intracellular calcium dynamics through the detailed observation of calcium wave propagation within a dendrite.Significance.ARES stands out as a robust and precise tool for the quantification of fluorescence signals, adept at analyzing both spontaneous and evoked calcium dynamics. Its ability to facilitate the subcellular localization of calcium signals and the spatiotemporal tracking of calcium dynamics-where traditional ratiometric measures falter-underscores its potential to revolutionize baseline-independent analyses in the field.
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Affiliation(s)
- Niccolò Calcini
- Department of Neurophysiology, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Heyedaalseweg 135, Nijmegen 6525 HJ, The Netherlands
| | - Angelica da Silva Lantyer
- Department of Neurophysiology, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Heyedaalseweg 135, Nijmegen 6525 HJ, The Netherlands
| | - Fleur Zeldenrust
- Department of Neurophysiology, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Heyedaalseweg 135, Nijmegen 6525 HJ, The Netherlands
| | - Tansu Celikel
- Department of Neurophysiology, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Heyedaalseweg 135, Nijmegen 6525 HJ, The Netherlands
- School of Psychology, Georgia Institute of Technology, 654 Cherry Street, Atlanta, GA 30332, United States of America
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8
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Kogan JF, Fontanini A. Learning enhances representations of taste-guided decisions in the mouse gustatory insular cortex. Curr Biol 2024; 34:1880-1892.e5. [PMID: 38631343 PMCID: PMC11188718 DOI: 10.1016/j.cub.2024.03.034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Revised: 02/07/2024] [Accepted: 03/19/2024] [Indexed: 04/19/2024]
Abstract
Learning to discriminate overlapping gustatory stimuli that predict distinct outcomes-a feat known as discrimination learning-can mean the difference between ingesting a poison or a nutritive meal. Despite the obvious importance of this process, very little is known about the neural basis of taste discrimination learning. In other sensory modalities, this form of learning can be mediated by either the sharpening of sensory representations or the enhanced ability of "decision-making" circuits to interpret sensory information. Given the dual role of the gustatory insular cortex (GC) in encoding both sensory and decision-related variables, this region represents an ideal site for investigating how neural activity changes as animals learn a novel taste discrimination. Here, we present results from experiments relying on two-photon calcium imaging of GC neural activity in mice performing a taste-guided mixture discrimination task. The task allows for the recording of neural activity before and after learning induced by training mice to discriminate increasingly similar pairs of taste mixtures. Single-neuron and population analyses show a time-varying pattern of activity, with early sensory responses emerging after taste delivery and binary, choice-encoding responses emerging later in the delay before a decision is made. Our results demonstrate that, while both sensory and decision-related information is encoded by GC in the context of a taste mixture discrimination task, learning and improved performance are associated with a specific enhancement of decision-related responses.
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Affiliation(s)
- Joshua F Kogan
- Graduate Program in Neuroscience, Stony Brook University, Stony Brook, NY 11794, USA; Medical Scientist Training Program, Stony Brook University, Stony Brook, NY 11794, USA; Department of Neurobiology and Behavior, Stony Brook University, Stony Brook, NY 11794, USA.
| | - Alfredo Fontanini
- Graduate Program in Neuroscience, Stony Brook University, Stony Brook, NY 11794, USA; Medical Scientist Training Program, Stony Brook University, Stony Brook, NY 11794, USA; Department of Neurobiology and Behavior, Stony Brook University, Stony Brook, NY 11794, USA.
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9
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Azrad Leibovitch T, Farah N, Markus A, Mandel Y. A novel GCaMP6f-RCS rat model for studying electrical stimulation in the degenerated retina. Front Cell Dev Biol 2024; 12:1386141. [PMID: 38711618 PMCID: PMC11070775 DOI: 10.3389/fcell.2024.1386141] [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: 02/14/2024] [Accepted: 03/25/2024] [Indexed: 05/08/2024] Open
Abstract
Background: Retinal prostheses aim to restore vision by electrically stimulating the remaining viable retinal cells in Retinal Degeneration (RD) cases. Research in this field necessitates a comprehensive analysis of retinal ganglion cells' (RGCs) responses to assess the obtained visual acuity and quality. Here we present a novel animal model which facilitates the optical recording of RGCs activity in an RD rat. This model can significantly enhance the functional evaluation of vision restoration treatments. Methods: The development of the novel rat model is based on crossbreeding a retinal degenerated Royal College of Surgeons (RCS) rat with a transgenic line expressing the genetic calcium indicator GCaMP6f in the RGCs. Characterization of the model was achieved using Optical Coherence Tomography (OCT) imaging, histology, and electroretinography (ERG) at the ages of 4, 8, and 12 weeks. Additionally, optical recordings of RGCs function in response to ex-vivo subretinal electrical stimulations were performed. Results: Histological investigations confirmed the high expression of GCaMP6f in the RGCs and minimal expression in the inner nuclear layer (INL). OCT imaging and histological studies revealed the expected gradual retinal degeneration, as evident by the decrease in retinal thickness with age and the formation of subretinal debris. This degeneration was further confirmed by ERG recordings, which demonstrated a significant decrease in the b-wave amplitude throughout the degeneration process, culminating in its absence at 12 weeks in the GCaMP6f-RCS rat. Importantly, the feasibility of investigating subretinal stimulation was demonstrated, revealing a consistent increase in activation threshold throughout degeneration. Furthermore, an increase in the diameter of the activated area with increasing currents was observed. The spatial spread of the activation area in the GCaMP6f-RCS rat was found to be smaller and exhibited faster activation dynamics compared with the GCaMP6f-LE strain. Conclusion: This novel animal model offers an opportunity to deepen our understanding of prosthetically induced retinal responses, potentially leading to significant advancements in prosthetic interventions in visual impairments.
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Affiliation(s)
- Tamar Azrad Leibovitch
- Bar Ilan Institute for Nanotechnology and Advanced Materials (BINA), Bar Ilan University, Ramat Gan, Israel
- Faculty of Life Sciences, School of Optometry and Visual Science, Bar Ilan University, Ramat Gan, Israel
| | - Nairouz Farah
- Bar Ilan Institute for Nanotechnology and Advanced Materials (BINA), Bar Ilan University, Ramat Gan, Israel
- Faculty of Life Sciences, School of Optometry and Visual Science, Bar Ilan University, Ramat Gan, Israel
| | - Amos Markus
- Bar Ilan Institute for Nanotechnology and Advanced Materials (BINA), Bar Ilan University, Ramat Gan, Israel
- Faculty of Life Sciences, School of Optometry and Visual Science, Bar Ilan University, Ramat Gan, Israel
| | - Yossi Mandel
- Bar Ilan Institute for Nanotechnology and Advanced Materials (BINA), Bar Ilan University, Ramat Gan, Israel
- Faculty of Life Sciences, School of Optometry and Visual Science, Bar Ilan University, Ramat Gan, Israel
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10
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Celinskis D, Black CJ, Murphy J, Barrios-Anderson A, Friedman NG, Shaner NC, Saab CY, Gomez-Ramirez M, Borton DA, Moore CI. Toward a brighter constellation: multiorgan neuroimaging of neural and vascular dynamics in the spinal cord and brain. NEUROPHOTONICS 2024; 11:024209. [PMID: 38725801 PMCID: PMC11079446 DOI: 10.1117/1.nph.11.2.024209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 03/18/2024] [Accepted: 03/19/2024] [Indexed: 05/12/2024]
Abstract
Significance Pain comprises a complex interaction between motor action and somatosensation that is dependent on dynamic interactions between the brain and spinal cord. This makes understanding pain particularly challenging as it involves rich interactions between many circuits (e.g., neural and vascular) and signaling cascades throughout the body. As such, experimentation on a single region may lead to an incomplete and potentially incorrect understanding of crucial underlying mechanisms. Aim We aimed to develop and validate tools to enable detailed and extended observation of neural and vascular activity in the brain and spinal cord. The first key set of innovations was targeted to developing novel imaging hardware that addresses the many challenges of multisite imaging. The second key set of innovations was targeted to enabling bioluminescent (BL) imaging, as this approach can address limitations of fluorescent microscopy including photobleaching, phototoxicity, and decreased resolution due to scattering of excitation signals. Approach We designed 3D-printed brain and spinal cord implants to enable effective surgical implantations and optical access with wearable miniscopes or an open window (e.g., for one- or two-photon microscopy or optogenetic stimulation). We also tested the viability for BL imaging and developed a novel modified miniscope optimized for these signals (BLmini). Results We describe "universal" implants for acute and chronic simultaneous brain-spinal cord imaging and optical stimulation. We further describe successful imaging of BL signals in both foci and a new miniscope, the "BLmini," which has reduced weight, cost, and form-factor relative to standard wearable miniscopes. Conclusions The combination of 3D-printed implants, advanced imaging tools, and bioluminescence imaging techniques offers a coalition of methods for understanding spinal cord-brain interactions. Our work has the potential for use in future research into neuropathic pain and other sensory disorders and motor behavior.
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Affiliation(s)
- Dmitrijs Celinskis
- Carney Institute for Brain Science, Providence, Rhode Island, United States
| | | | - Jeremy Murphy
- Carney Institute for Brain Science, Providence, Rhode Island, United States
| | | | - Nina G. Friedman
- Carney Institute for Brain Science, Providence, Rhode Island, United States
| | - Nathan C. Shaner
- University of California San Diego, School of Medicine, La Jolla, California, United States
| | - Carl Y. Saab
- Cleveland Clinic Lerner Research Institute, Neurological Institute, Department of Biomedical Engineering, Cleveland, Ohio, United States
| | - Manuel Gomez-Ramirez
- University of Rochester, School of Arts and Sciences, Rochester, New York, United States
| | - David A. Borton
- Carney Institute for Brain Science, Providence, Rhode Island, United States
- Brown University, School of Engineering, Providence, Rhode Island, United States
- Center for Neurorestoration and Neurotechnology, Providence VA Medical Center, Providence, Rhode Island, United States
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11
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Zhang Y, Looger LL. Fast and sensitive GCaMP calcium indicators for neuronal imaging. J Physiol 2024; 602:1595-1604. [PMID: 36811153 DOI: 10.1113/jp283832] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2022] [Accepted: 02/15/2023] [Indexed: 02/24/2023] Open
Abstract
We review the principles of development and deployment of genetically encoded calcium indicators (GECIs) for the detection of neural activity. Our focus is on the popular GCaMP family of green GECIs, culminating in the recent release of the jGCaMP8 sensors, with dramatically improved kinetics relative to previous generations. We summarize the properties of GECIs in multiple colour channels (blue, cyan, green, yellow, red, far-red) and highlight areas for further improvement. With their low-millisecond rise-times, the jGCaMP8 indicators allow new classes of experiments following neural activity in time frames approaching the underlying computations.
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Affiliation(s)
- Yan Zhang
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Loren L Looger
- Department of Neurosciences, Howard Hughes Medical Institute, University of California, San Diego, La Jolla, CA, USA
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12
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Cheng N, Dong Q, Zhang Z, Wang L, Chen X, Wang C. Egocentric processing of items in spines, dendrites, and somas in the retrosplenial cortex. Neuron 2024; 112:646-660.e8. [PMID: 38101396 DOI: 10.1016/j.neuron.2023.11.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2023] [Revised: 08/31/2023] [Accepted: 11/15/2023] [Indexed: 12/17/2023]
Abstract
Egocentric representations of external items are essential for spatial navigation and memory. Here, we explored the neural mechanisms underlying egocentric processing in the retrosplenial cortex (RSC), a pivotal area for memory and navigation. Using one-photon and two-photon calcium imaging, we identified egocentric tuning for environment boundaries in dendrites, spines, and somas of RSC neurons (egocentric boundary cells) in the open-field task. Dendrites with egocentric tuning tended to have similarly tuned spines. We further identified egocentric neurons representing landmarks in a virtual navigation task or remembered cue location in a goal-oriented task, respectively. These neurons formed an independent population with egocentric boundary cells, suggesting that dedicated neurons with microscopic clustering of functional inputs shaped egocentric boundary processing in RSC and that RSC adopted a labeled line code with distinct classes of egocentric neurons responsible for representing different items in specific behavioral contexts, which could lead to efficient and flexible computation.
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Affiliation(s)
- Ning Cheng
- Shenzhen Key Laboratory of Precision Diagnosis and Treatment of Depression, Shenzhen-Hong Kong Institute of Brain Science, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; CAS Key Laboratory of Brain Connectome and Manipulation, the Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, the Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Qiqi Dong
- Shenzhen Key Laboratory of Precision Diagnosis and Treatment of Depression, Shenzhen-Hong Kong Institute of Brain Science, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; CAS Key Laboratory of Brain Connectome and Manipulation, the Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, the Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Zhen Zhang
- CAS Key Laboratory of Brain Connectome and Manipulation, the Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, the Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Li Wang
- Brain Research Centre, Department of Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518055, China
| | - Xiaojing Chen
- Brain Research Centre, Department of Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518055, China.
| | - Cheng Wang
- Shenzhen Key Laboratory of Precision Diagnosis and Treatment of Depression, Shenzhen-Hong Kong Institute of Brain Science, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; CAS Key Laboratory of Brain Connectome and Manipulation, the Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, the Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; CAS Centre for Excellence in Brain Science and Intelligent Technology, Shanghai, China.
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13
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Seitzman BA, Reynoso FJ, Mitchell TJ, Bice AR, Jarang A, Wang X, Mpoy C, Strong L, Rogers BE, Yuede CM, Rubin JB, Perkins SM, Bauer AQ. Functional network disorganization and cognitive decline following fractionated whole-brain radiation in mice. GeroScience 2024; 46:543-562. [PMID: 37749370 PMCID: PMC10828348 DOI: 10.1007/s11357-023-00944-w] [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: 08/18/2023] [Accepted: 09/11/2023] [Indexed: 09/27/2023] Open
Abstract
Cognitive dysfunction following radiotherapy (RT) is one of the most common complications associated with RT delivered to the brain, but the precise mechanisms behind this dysfunction are not well understood, and to date, there are no preventative measures or effective treatments. To improve patient outcomes, a better understanding of the effects of radiation on the brain's functional systems is required. Functional magnetic resonance imaging (fMRI) has shown promise in this regard, however, compared to neural activity, hemodynamic measures of brain function are slow and indirect. Understanding how RT acutely and chronically affects functional brain organization requires more direct examination of temporally evolving neural dynamics as they relate to cerebral hemodynamics for bridging with human studies. In order to adequately study the underlying mechanisms of RT-induced cognitive dysfunction, the development of clinically mimetic RT protocols in animal models is needed. To address these challenges, we developed a fractionated whole-brain RT protocol (3Gy/day for 10 days) and applied longitudinal wide field optical imaging (WFOI) of neural and hemodynamic brain activity at 1, 2, and 3 months post RT. At each time point, mice were subject to repeated behavioral testing across a variety of sensorimotor and cognitive domains. Disruptions in cortical neuronal and hemodynamic activity observed 1 month post RT were significantly worsened by 3 months. While broad changes were observed in functional brain organization post RT, brain regions most impacted by RT occurred within those overlapping with the mouse default mode network and other association areas similar to prior reports in human subjects. Further, significant cognitive deficits were observed following tests of novel object investigation and responses to auditory and contextual cues after fear conditioning. Our results fill a much-needed gap in understanding the effects of whole-brain RT on systems level brain organization and how RT affects neuronal versus hemodynamic signaling in the cortex. Having established a clinically-relevant injury model, future studies can examine therapeutic interventions designed to reduce neuroinflammation-based injury following RT. Given the overlap of sequelae that occur following RT with and without chemotherapy, these tools can also be easily incorporated to examine chemotherapy-related cognitive impairment.
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Affiliation(s)
- Benjamin A Seitzman
- Department of Radiation Oncology, School of Medicine, Washington University in St. Louis, 4921 Parkview Place, Campus Box 8224, St. Louis, MO, 63110, USA
| | - Francisco J Reynoso
- Department of Radiation Oncology, School of Medicine, Washington University in St. Louis, 4921 Parkview Place, Campus Box 8224, St. Louis, MO, 63110, USA
| | - Timothy J Mitchell
- Department of Radiation Oncology, School of Medicine, Washington University in St. Louis, 4921 Parkview Place, Campus Box 8224, St. Louis, MO, 63110, USA
| | - Annie R Bice
- Mallinckrodt Institute of Radiology, School of Medicine, Washington University in St. Louis, 660 S. Euclid Ave, Campus Box 8225, St. Louis, MO, 63110, USA
| | - Anmol Jarang
- Mallinckrodt Institute of Radiology, School of Medicine, Washington University in St. Louis, 660 S. Euclid Ave, Campus Box 8225, St. Louis, MO, 63110, USA
| | - Xiaodan Wang
- Mallinckrodt Institute of Radiology, School of Medicine, Washington University in St. Louis, 660 S. Euclid Ave, Campus Box 8225, St. Louis, MO, 63110, USA
- Department of Biomedical Engineering, McKelvey School of Engineering, Washington University in St. Louis, St. Louis, MO, USA
| | - Cedric Mpoy
- Department of Radiation Oncology, School of Medicine, Washington University in St. Louis, 4921 Parkview Place, Campus Box 8224, St. Louis, MO, 63110, USA
| | - Lori Strong
- Department of Radiation Oncology, School of Medicine, Washington University in St. Louis, 4921 Parkview Place, Campus Box 8224, St. Louis, MO, 63110, USA
| | - Buck E Rogers
- Department of Radiation Oncology, School of Medicine, Washington University in St. Louis, 4921 Parkview Place, Campus Box 8224, St. Louis, MO, 63110, USA
| | - Carla M Yuede
- Department of Psychiatry, School of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Joshua B Rubin
- Department of Pediatrics, School of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Stephanie M Perkins
- Department of Radiation Oncology, School of Medicine, Washington University in St. Louis, 4921 Parkview Place, Campus Box 8224, St. Louis, MO, 63110, USA.
| | - Adam Q Bauer
- Mallinckrodt Institute of Radiology, School of Medicine, Washington University in St. Louis, 660 S. Euclid Ave, Campus Box 8225, St. Louis, MO, 63110, USA.
- Department of Biomedical Engineering, McKelvey School of Engineering, Washington University in St. Louis, St. Louis, MO, USA.
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14
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Gutzen R, De Bonis G, De Luca C, Pastorelli E, Capone C, Allegra Mascaro AL, Resta F, Manasanch A, Pavone FS, Sanchez-Vives MV, Mattia M, Grün S, Paolucci PS, Denker M. A modular and adaptable analysis pipeline to compare slow cerebral rhythms across heterogeneous datasets. CELL REPORTS METHODS 2024; 4:100681. [PMID: 38183979 PMCID: PMC10831958 DOI: 10.1016/j.crmeth.2023.100681] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Revised: 08/11/2023] [Accepted: 12/11/2023] [Indexed: 01/08/2024]
Abstract
Neuroscience is moving toward a more integrative discipline where understanding brain function requires consolidating the accumulated evidence seen across experiments, species, and measurement techniques. A remaining challenge on that path is integrating such heterogeneous data into analysis workflows such that consistent and comparable conclusions can be distilled as an experimental basis for models and theories. Here, we propose a solution in the context of slow-wave activity (<1 Hz), which occurs during unconscious brain states like sleep and general anesthesia and is observed across diverse experimental approaches. We address the issue of integrating and comparing heterogeneous data by conceptualizing a general pipeline design that is adaptable to a variety of inputs and applications. Furthermore, we present the Collaborative Brain Wave Analysis Pipeline (Cobrawap) as a concrete, reusable software implementation to perform broad, detailed, and rigorous comparisons of slow-wave characteristics across multiple, openly available electrocorticography (ECoG) and calcium imaging datasets.
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Affiliation(s)
- Robin Gutzen
- Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA-Institute Brain Structure-Function Relationships (INM-10), Jülich Research Centre, Jülich, Germany; Theoretical Systems Neurobiology, RWTH Aachen University, Aachen, Germany.
| | - Giulia De Bonis
- Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Roma, Rome, Italy
| | - Chiara De Luca
- Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Roma, Rome, Italy; Institute of Neuroinformatics, University of Zürich and ETH Zürich, Zürich, Switzerland
| | - Elena Pastorelli
- Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Roma, Rome, Italy
| | - Cristiano Capone
- Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Roma, Rome, Italy
| | - Anna Letizia Allegra Mascaro
- European Laboratory for Non-linear Spectroscopy (LENS), University of Florence, Florence, Italy; Neuroscience Institute, National Research Council, Pisa, Italy
| | - Francesco Resta
- European Laboratory for Non-linear Spectroscopy (LENS), University of Florence, Florence, Italy; Department of Physics and Astronomy, University of Florence, Florence, Italy
| | - Arnau Manasanch
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Francesco Saverio Pavone
- European Laboratory for Non-linear Spectroscopy (LENS), University of Florence, Florence, Italy; Department of Physics and Astronomy, University of Florence, Florence, Italy; National Institute of Optics, National Research Council, Sesto Fiorentino, Italy
| | - Maria V Sanchez-Vives
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
| | - Maurizio Mattia
- National Center for Radiation Protection and Computational Physics, Istituto Superiore di Sanità (ISS), Rome, Italy
| | - Sonja Grün
- Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA-Institute Brain Structure-Function Relationships (INM-10), Jülich Research Centre, Jülich, Germany; Theoretical Systems Neurobiology, RWTH Aachen University, Aachen, Germany
| | | | - Michael Denker
- Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA-Institute Brain Structure-Function Relationships (INM-10), Jülich Research Centre, Jülich, Germany
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15
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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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16
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Tiroshi L, Atamna Y, Gilin N, Berkowitz N, Goldberg JA. Striatal Neurons Are Recruited Dynamically into Collective Representations of Self-Initiated and Learned Actions in Freely Moving Mice. eNeuro 2024; 11:ENEURO.0315-23.2023. [PMID: 38164559 PMCID: PMC11057506 DOI: 10.1523/eneuro.0315-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Revised: 11/05/2023] [Accepted: 11/17/2023] [Indexed: 01/03/2024] Open
Abstract
Striatal spiny projection neurons are hyperpolarized-at-rest (HaR) and driven to action potential threshold by a small number of powerful inputs-an input-output configuration that is detrimental to response reliability. Because the striatum is important for habitual behaviors and goal-directed learning, we conducted a microendoscopic imaging in freely moving mice that express a genetically encoded Ca2+ indicator sparsely in striatal HaR neurons to evaluate their response reliability during self-initiated movements and operant conditioning. The sparse expression was critical for longitudinal studies of response reliability, and for studying correlations among HaR neurons while minimizing spurious correlations arising from contamination by the background signal. We found that HaR neurons are recruited dynamically into action representation, with distinct neuronal subsets being engaged in a moment-by-moment fashion. While individual neurons respond with little reliability, the population response remained stable across days. Moreover, we found evidence for the temporal coupling between neuronal subsets during conditioned (but not innate) behaviors.
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Affiliation(s)
- Lior Tiroshi
- Department of Medical Neurobiology, Institute of Medical Research Israel - Canada, The Faculty of Medicine, The Hebrew University of Jerusalem, 9112102, Jerusalem, Israel
| | - Yara Atamna
- Department of Medical Neurobiology, Institute of Medical Research Israel - Canada, The Faculty of Medicine, The Hebrew University of Jerusalem, 9112102, Jerusalem, Israel
| | - Naomi Gilin
- Department of Medical Neurobiology, Institute of Medical Research Israel - Canada, The Faculty of Medicine, The Hebrew University of Jerusalem, 9112102, Jerusalem, Israel
| | - Noa Berkowitz
- Department of Medical Neurobiology, Institute of Medical Research Israel - Canada, The Faculty of Medicine, The Hebrew University of Jerusalem, 9112102, Jerusalem, Israel
| | - Joshua A Goldberg
- Department of Medical Neurobiology, Institute of Medical Research Israel - Canada, The Faculty of Medicine, The Hebrew University of Jerusalem, 9112102, Jerusalem, Israel
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17
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Celinskis D, Black CJ, Murphy J, Barrios-Anderson A, Friedman N, Shaner NC, Saab C, Gomez-Ramirez M, Lipscombe D, Borton DA, Moore CI. Towards a Brighter Constellation: Multi-Organ Neuroimaging of Neural and Vascular Dynamics in the Spinal Cord and Brain. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.25.573323. [PMID: 38234789 PMCID: PMC10793404 DOI: 10.1101/2023.12.25.573323] [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
Significance Pain is comprised of a complex interaction between motor action and somatosensation that is dependent on dynamic interactions between the brain and spinal cord. This makes understanding pain particularly challenging as it involves rich interactions between many circuits (e.g., neural and vascular) and signaling cascades throughout the body. As such, experimentation on a single region may lead to an incomplete and potentially incorrect understanding of crucial underlying mechanisms. Aim Here, we aimed to develop and validate new tools to enable detailed and extended observation of neural and vascular activity in the brain and spinal cord. The first key set of innovations were targeted to developing novel imaging hardware that addresses the many challenges of multi-site imaging. The second key set of innovations were targeted to enabling bioluminescent imaging, as this approach can address limitations of fluorescent microscopy including photobleaching, phototoxicity and decreased resolution due to scattering of excitation signals. Approach We designed 3D-printed brain and spinal cord implants to enable effective surgical implantations and optical access with wearable miniscopes or an open window (e.g., for one- or two-photon microscopy or optogenetic stimulation). We also tested the viability for bioluminescent imaging, and developed a novel modified miniscope optimized for these signals (BLmini). Results Here, we describe novel 'universal' implants for acute and chronic simultaneous brain-spinal cord imaging and optical stimulation. We further describe successful imaging of bioluminescent signals in both foci, and a new miniscope, the 'BLmini,' which has reduced weight, cost and form-factor relative to standard wearable miniscopes. Conclusions The combination of 3D printed implants, advanced imaging tools, and bioluminescence imaging techniques offers a new coalition of methods for understanding spinal cord-brain interactions. This work has the potential for use in future research into neuropathic pain and other sensory disorders and motor behavior.
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Affiliation(s)
| | | | - Jeremy Murphy
- Carney Institute for Brain Science, Providence, RI, USA
| | | | - Nina Friedman
- Carney Institute for Brain Science, Providence, RI, USA
| | - Nathan C. Shaner
- University of California San Diego School of Medicine, La Jolla, CA, USA
| | - Carl Saab
- Cleveland Clinic Lerner Research Institute, Department of Biomedical Engineering and Neurological Institute, Cleveland, OH, USA
| | | | | | - David A. Borton
- Carney Institute for Brain Science, Providence, RI, USA
- School of Engineering, Brown University, RI, USA
- Center for Neurorestoration and Neurotechnology, Providence VA Medical Center, RI, USA
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18
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Fiore F, Alhalaseh K, Dereddi RR, Bodaleo Torres F, Çoban I, Harb A, Agarwal A. Norepinephrine regulates calcium signals and fate of oligodendrocyte precursor cells in the mouse cerebral cortex. Nat Commun 2023; 14:8122. [PMID: 38065932 PMCID: PMC10709653 DOI: 10.1038/s41467-023-43920-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Accepted: 11/24/2023] [Indexed: 12/18/2023] Open
Abstract
Oligodendrocyte precursor cells (OPCs) generate oligodendrocytes, contributing to myelination and myelin repair. OPCs contact axons and respond to neuronal activity, but how the information relayed by the neuronal activity translates into OPC Ca2+ signals, which in turn influence their fate, remains unknown. We generated transgenic mice for concomitant monitoring of OPCs Ca2+ signals and cell fate using 2-photon microscopy in the somatosensory cortex of awake-behaving mice. Ca2+ signals in OPCs mainly occur within processes and confine to Ca2+ microdomains. A subpopulation of OPCs enhances Ca2+ transients while mice engaged in exploratory locomotion. We found that OPCs responsive to locomotion preferentially differentiate into oligodendrocytes, and locomotion-non-responsive OPCs divide. Norepinephrine mediates locomotion-evoked Ca2+ increases in OPCs by activating α1 adrenergic receptors, and chemogenetic activation of OPCs or noradrenergic neurons promotes OPC differentiation. Hence, we uncovered that for fate decisions OPCs integrate Ca2+ signals, and norepinephrine is a potent regulator of OPC fate.
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Affiliation(s)
- Frederic Fiore
- The Chica and Heinz Schaller Research Group, Institute for Anatomy and Cell Biology, Heidelberg University, Heidelberg, Germany
| | - Khaleel Alhalaseh
- The Chica and Heinz Schaller Research Group, Institute for Anatomy and Cell Biology, Heidelberg University, Heidelberg, Germany
| | - Ram R Dereddi
- The Chica and Heinz Schaller Research Group, Institute for Anatomy and Cell Biology, Heidelberg University, Heidelberg, Germany
- Interdisciplinary Center for Neurosciences, Heidelberg University, Heidelberg, Germany
| | - Felipe Bodaleo Torres
- The Chica and Heinz Schaller Research Group, Institute for Anatomy and Cell Biology, Heidelberg University, Heidelberg, Germany
| | - Ilknur Çoban
- The Chica and Heinz Schaller Research Group, Institute for Anatomy and Cell Biology, Heidelberg University, Heidelberg, Germany
- Interdisciplinary Center for Neurosciences, Heidelberg University, Heidelberg, Germany
| | - Ali Harb
- The Chica and Heinz Schaller Research Group, Institute for Anatomy and Cell Biology, Heidelberg University, Heidelberg, Germany
| | - Amit Agarwal
- The Chica and Heinz Schaller Research Group, Institute for Anatomy and Cell Biology, Heidelberg University, Heidelberg, Germany.
- Interdisciplinary Center for Neurosciences, Heidelberg University, Heidelberg, Germany.
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19
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Rubinov M. Circular and unified analysis in network neuroscience. eLife 2023; 12:e79559. [PMID: 38014843 PMCID: PMC10684154 DOI: 10.7554/elife.79559] [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: 04/18/2022] [Accepted: 10/18/2023] [Indexed: 11/29/2023] Open
Abstract
Genuinely new discovery transcends existing knowledge. Despite this, many analyses in systems neuroscience neglect to test new speculative hypotheses against benchmark empirical facts. Some of these analyses inadvertently use circular reasoning to present existing knowledge as new discovery. Here, I discuss that this problem can confound key results and estimate that it has affected more than three thousand studies in network neuroscience over the last decade. I suggest that future studies can reduce this problem by limiting the use of speculative evidence, integrating existing knowledge into benchmark models, and rigorously testing proposed discoveries against these models. I conclude with a summary of practical challenges and recommendations.
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Affiliation(s)
- Mika Rubinov
- Departments of Biomedical Engineering, Computer Science, and Psychology, Vanderbilt UniversityNashvilleUnited States
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
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20
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Abghari M, Vu JTCM, Eckberg N, Aldana BI, Kohlmeier KA. Decanoic Acid Rescues Differences in AMPA-Mediated Calcium Rises in Hippocampal CA1 Astrocytes and Neurons in the 5xFAD Mouse Model of Alzheimer's Disease. Biomolecules 2023; 13:1461. [PMID: 37892143 PMCID: PMC10604953 DOI: 10.3390/biom13101461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 09/13/2023] [Accepted: 09/22/2023] [Indexed: 10/29/2023] Open
Abstract
Alzheimer's disease (AD), a devastating neurodegenerative disease characterized by cognitive dysfunctions, is associated with high levels of amyloid beta 42 (Aβ42), which is believed to play a role in cellular damage and signaling changes in AD. Decanoic acid has been shown to be therapeutic in AD. Glutamatergic signaling within neurons and astrocytes of the CA1 region of the hippocampus is critical in cognitive processes, and previous work has indicated deficiencies in this signaling in a mouse model of AD. In this study, we investigated glutamate-mediated signaling by evaluating AMPA-mediated calcium rises in female and male CA1 neurons and astrocytes in a mouse model of AD and examined the potential of decanoic acid to normalize this signaling. In brain slices from 5xFAD mice in which there are five mutations leading to increasing levels of Aβ42, AMPA-mediated calcium transients in CA1 neurons and astrocytes were significantly lower than that seen in wildtype controls in both females and males. Interestingly, incubation of 5xFAD slices in decanoic acid restored AMPA-mediated calcium levels in neurons and astrocytes in both females and males to levels indistinguishable from those seen in wildtype, whereas similar exposure to decanoic acid did not result in changes in AMPA-mediated transients in neurons or astrocytes in either sex in the wildtype. Our data indicate that one mechanism by which decanoic acid could improve cognitive functioning is through normalizing AMPA-mediated signaling in CA1 hippocampal cells.
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21
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Ferguson KA, Salameh J, Alba C, Selwyn H, Barnes C, Lohani S, Cardin JA. VIP interneurons regulate cortical size tuning and visual perception. Cell Rep 2023; 42:113088. [PMID: 37682710 PMCID: PMC10618959 DOI: 10.1016/j.celrep.2023.113088] [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: 05/08/2023] [Revised: 07/12/2023] [Accepted: 08/17/2023] [Indexed: 09/10/2023] Open
Abstract
Cortical circuit function is regulated by extensively interconnected, diverse populations of GABAergic interneurons that may play key roles in shaping circuit operation according to behavioral context. A specialized population of interneurons that co-express vasoactive intestinal peptides (VIP-INs) are activated during arousal and innervate other INs and pyramidal neurons (PNs). Although state-dependent modulation of VIP-INs has been extensively studied, their role in regulating sensory processing is less well understood. We examined the impact of VIP-INs in the primary visual cortex of awake behaving mice. Loss of VIP-IN activity alters the behavioral state-dependent modulation of somatostatin-expressing INs (SST-INs) but not PNs. In contrast, reduced VIP-IN activity globally disrupts visual feature selectivity for stimulus size. Moreover, the impact of VIP-INs on perceptual behavior varies with context and is more acute for small than large visual cues. VIP-INs thus contribute to both state-dependent modulation of cortical activity and sensory context-dependent perceptual performance.
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Affiliation(s)
- Katie A Ferguson
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Jenna Salameh
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Christopher Alba
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Hannah Selwyn
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Clayton Barnes
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Sweyta Lohani
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Jessica A Cardin
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510, USA.
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22
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Atanas AA, Kim J, Wang Z, Bueno E, Becker M, Kang D, Park J, Kramer TS, Wan FK, Baskoylu S, Dag U, Kalogeropoulou E, Gomes MA, Estrem C, Cohen N, Mansinghka VK, Flavell SW. Brain-wide representations of behavior spanning multiple timescales and states in C. elegans. Cell 2023; 186:4134-4151.e31. [PMID: 37607537 PMCID: PMC10836760 DOI: 10.1016/j.cell.2023.07.035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 07/05/2023] [Accepted: 07/28/2023] [Indexed: 08/24/2023]
Abstract
Changes in an animal's behavior and internal state are accompanied by widespread changes in activity across its brain. However, how neurons across the brain encode behavior and how this is impacted by state is poorly understood. We recorded brain-wide activity and the diverse motor programs of freely moving C. elegans and built probabilistic models that explain how each neuron encodes quantitative behavioral features. By determining the identities of the recorded neurons, we created an atlas of how the defined neuron classes in the C. elegans connectome encode behavior. Many neuron classes have conjunctive representations of multiple behaviors. Moreover, although many neurons encode current motor actions, others integrate recent actions. Changes in behavioral state are accompanied by widespread changes in how neurons encode behavior, and we identify these flexible nodes in the connectome. Our results provide a global map of how the cell types across an animal's brain encode its behavior.
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Affiliation(s)
- Adam A Atanas
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Computational and Systems Biology Program, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jungsoo Kim
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Ziyu Wang
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Eric Bueno
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - McCoy Becker
- Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Di Kang
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jungyeon Park
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Talya S Kramer
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA; MIT Biology Graduate Program, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Flossie K Wan
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Saba Baskoylu
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Ugur Dag
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Elpiniki Kalogeropoulou
- School of Computing, University of Leeds, Leeds, UK; School of Biology, University of Leeds, Leeds, UK
| | - Matthew A Gomes
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Cassi Estrem
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Netta Cohen
- School of Computing, University of Leeds, Leeds, UK
| | - Vikash K Mansinghka
- Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Steven W Flavell
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.
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23
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McGregor JN, Farris CA, Ensley S, Schneider A, Wang C, Liu Y, Tu J, Elmore H, Ronayne KD, Wessel R, Dyer EL, Bhaskaran-Nair K, Holtzman DM, Hengen KB. Tauopathy severely disrupts homeostatic set-points in emergent neural dynamics but not in the activity of individual neurons. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.01.555947. [PMID: 37732214 PMCID: PMC10508737 DOI: 10.1101/2023.09.01.555947] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/22/2023]
Abstract
The homeostatic regulation of neuronal activity is essential for robust computation; key set-points, such as firing rate, are actively stabilized to compensate for perturbations. From this perspective, the disruption of brain function central to neurodegenerative disease should reflect impairments of computationally essential set-points. Despite connecting neurodegeneration to functional outcomes, the impact of disease on set-points in neuronal activity is unknown. Here we present a comprehensive, theory-driven investigation of the effects of tau-mediated neurodegeneration on homeostatic set-points in neuronal activity. In a mouse model of tauopathy, we examine 27,000 hours of hippocampal recordings during free behavior throughout disease progression. Contrary to our initial hypothesis that tauopathy would impact set-points in spike rate and variance, we found that cell-level set-points are resilient to even the latest stages of disease. Instead, we find that tauopathy disrupts neuronal activity at the network-level, which we quantify using both pairwise measures of neuron interactions as well as measurement of the network's nearness to criticality, an ideal computational regime that is known to be a homeostatic set-point. We find that shifts in network criticality 1) track with symptoms, 2) predict underlying anatomical and molecular pathology, 3) occur in a sleep/wake dependent manner, and 4) can be used to reliably classify an animal's genotype. Our data suggest that the critical set-point is intact, but that homeostatic machinery is progressively incapable of stabilizing hippocampal networks, particularly during waking. This work illustrates how neurodegenerative processes can impact the computational capacity of neurobiological systems, and suggest an important connection between molecular pathology, circuit function, and animal behavior.
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Affiliation(s)
- James N McGregor
- Department of Biology, Washington University in Saint Louis, St. Louis, MO, USA
| | - Clayton A Farris
- Department of Biology, Washington University in Saint Louis, St. Louis, MO, USA
| | - Sahara Ensley
- Department of Biology, Washington University in Saint Louis, St. Louis, MO, USA
| | - Aidan Schneider
- Department of Biology, Washington University in Saint Louis, St. Louis, MO, USA
| | - Chao Wang
- Department of Neurology, Hope Center for Neurological Disorders, Knight Alzheimer's Disease Research Center, Washington University in Saint Louis, St. Louis, MO, USA
- Institute for Brain Science and Disease, Chongqing Medical University, 400016, Chongqing, China
| | - Yuqi Liu
- Department of Biology, Washington University in Saint Louis, St. Louis, MO, USA
| | - Jianhong Tu
- Department of Biology, Washington University in Saint Louis, St. Louis, MO, USA
| | - Halla Elmore
- Department of Biology, Washington University in Saint Louis, St. Louis, MO, USA
| | - Keenan D Ronayne
- Department of Biology, Washington University in Saint Louis, St. Louis, MO, USA
| | - Ralf Wessel
- Department of Physics, Washington University in Saint Louis, St. Louis, MO, USA
| | - Eva L Dyer
- Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | | | - David M Holtzman
- Department of Neurology, Hope Center for Neurological Disorders, Knight Alzheimer's Disease Research Center, Washington University in Saint Louis, St. Louis, MO, USA
| | - Keith B Hengen
- Department of Biology, Washington University in Saint Louis, St. Louis, MO, USA
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24
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Brynildsen JK, Rajan K, Henderson MX, Bassett DS. Network models to enhance the translational impact of cross-species studies. Nat Rev Neurosci 2023; 24:575-588. [PMID: 37524935 PMCID: PMC10634203 DOI: 10.1038/s41583-023-00720-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/17/2023] [Indexed: 08/02/2023]
Abstract
Neuroscience studies are often carried out in animal models for the purpose of understanding specific aspects of the human condition. However, the translation of findings across species remains a substantial challenge. Network science approaches can enhance the translational impact of cross-species studies by providing a means of mapping small-scale cellular processes identified in animal model studies to larger-scale inter-regional circuits observed in humans. In this Review, we highlight the contributions of network science approaches to the development of cross-species translational research in neuroscience. We lay the foundation for our discussion by exploring the objectives of cross-species translational models. We then discuss how the development of new tools that enable the acquisition of whole-brain data in animal models with cellular resolution provides unprecedented opportunity for cross-species applications of network science approaches for understanding large-scale brain networks. We describe how these tools may support the translation of findings across species and imaging modalities and highlight future opportunities. Our overarching goal is to illustrate how the application of network science tools across human and animal model studies could deepen insight into the neurobiology that underlies phenomena observed with non-invasive neuroimaging methods and could simultaneously further our ability to translate findings across species.
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Affiliation(s)
- Julia K Brynildsen
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Kanaka Rajan
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Michael X Henderson
- Parkinson's Disease Center, Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI, USA
| | - Dani S Bassett
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Electrical & Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Physics & Astronomy, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.
- Santa Fe Institute, Santa Fe, NM, USA.
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25
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Weber TD, Moya MV, Kılıç K, Mertz J, Economo MN. High-speed multiplane confocal microscopy for voltage imaging in densely labeled neuronal populations. Nat Neurosci 2023; 26:1642-1650. [PMID: 37604887 PMCID: PMC11209746 DOI: 10.1038/s41593-023-01408-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Accepted: 07/17/2023] [Indexed: 08/23/2023]
Abstract
Genetically encoded voltage indicators (GEVIs) hold immense potential for monitoring neuronal population activity. To date, best-in-class GEVIs rely on one-photon excitation. However, GEVI imaging of dense neuronal populations remains difficult because out-of-focus background fluorescence produces low contrast and excess noise when paired with conventional one-photon widefield imaging methods. To address this challenge, we developed an imaging system capable of efficient, high-contrast GEVI imaging at near-kHz rates and demonstrate it for in vivo and ex vivo imaging applications in the mouse neocortex. Our approach uses simultaneous multiplane imaging to monitor activity within contiguous tissue volumes with no penalty in speed or requirement for high excitation power. This approach, multi-Z imaging with confocal detection (MuZIC), permits high signal-to-noise ratio voltage imaging in densely labeled neuronal populations and is compatible with imaging through micro-optics. Moreover, it minimizes artifacts associated with concurrent imaging and optogenetic photostimulation for all-optical electrophysiology.
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Affiliation(s)
- Timothy D Weber
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Maria V Moya
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
- Center for Systems Neuroscience, Boston University, Boston, MA, USA
| | - Kıvılcım Kılıç
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
- Neurophotonics Center, Boston University, Boston, MA, USA
| | - Jerome Mertz
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
- Center for Systems Neuroscience, Boston University, Boston, MA, USA
- Neurophotonics Center, Boston University, Boston, MA, USA
- Photonics Center, Boston University, Boston, MA, USA
| | - Michael N Economo
- Department of Biomedical Engineering, Boston University, Boston, MA, USA.
- Center for Systems Neuroscience, Boston University, Boston, MA, USA.
- Neurophotonics Center, Boston University, Boston, MA, USA.
- Photonics Center, Boston University, Boston, MA, USA.
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26
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Scott A, Palmer D, Newell B, Lin I, Cayton CA, Paulson A, Remde P, Richard JM. Ventral Pallidal GABAergic Neuron Calcium Activity Encodes Cue-Driven Reward Seeking and Persists in the Absence of Reward Delivery. J Neurosci 2023; 43:5191-5203. [PMID: 37339880 PMCID: PMC10342224 DOI: 10.1523/jneurosci.0013-23.2023] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Revised: 06/01/2023] [Accepted: 06/10/2023] [Indexed: 06/22/2023] Open
Abstract
Reward-seeking behavior is often initiated by environmental cues that signal reward availability. This is a necessary behavioral response; however, cue reactivity and reward-seeking behavior can become maladaptive. To better understand how cue-elicited reward seeking becomes maladaptive, it is important to understand the neural circuits involved in assigning appetitive value to rewarding cues and actions. Ventral pallidum (VP) neurons are known to contribute to cue-elicited reward-seeking behavior and have heterogeneous responses in a discriminative stimulus (DS) task. The VP neuronal subtypes and output pathways that encode distinct aspects of the DS task remain unknown. Here, we used an intersectional viral approach with fiber photometry to record bulk calcium activity in VP GABAergic (VP GABA) neurons in male and female rats as they learned and performed the DS task. We found that VP GABA neurons are excited by reward-predictive cues but not neutral cues and that this response develops over time. We also found that this cue-evoked response predicts reward-seeking behavior and that inhibiting this VP GABA activity during cue presentation decreases reward-seeking behavior. Additionally, we found increased VP GABA calcium activity at the time of expected reward delivery, which occurred even on trials when reward was omitted. Together, these findings suggest that VP GABA neurons encode reward expectation, and calcium activity in these neurons encodes the vigor of cue-elicited reward seeking.SIGNIFICANCE STATEMENT VP circuitry is a major driver of cue-evoked behaviors. Previous work has found that VP neurons have heterogenous responses and contributions to reward-seeking behavior. This functional heterogeneity is because of differences of neurochemical subtypes and projections of VP neurons. Understanding the heterogenous responses among and within VP neuronal cell types is a necessary step in further understanding how cue-evoked behavior becomes maladaptive. Our work explores the canonical GABAergic VP neuron and how the calcium activity of these cells encodes components of cue-evoked reward seeking, including the vigor and persistence of reward seeking.
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Affiliation(s)
- Alexandra Scott
- Graduate Program in Neuroscience, University of Minnesota, Minneapolis, Minnesota 55455
- Medical Discovery Team on Addiction, University of Minnesota, Minneapolis, Minnesota 55455
| | - Dakota Palmer
- Graduate Program in Neuroscience, University of Minnesota, Minneapolis, Minnesota 55455
- Medical Discovery Team on Addiction, University of Minnesota, Minneapolis, Minnesota 55455
| | - Bailey Newell
- Medical Discovery Team on Addiction, University of Minnesota, Minneapolis, Minnesota 55455
- Department of Neuroscience, University of Minnesota, Minneapolis, Minnesota 55455
| | - Iris Lin
- Medical Discovery Team on Addiction, University of Minnesota, Minneapolis, Minnesota 55455
- Department of Neuroscience, University of Minnesota, Minneapolis, Minnesota 55455
| | - Christelle A Cayton
- Medical Discovery Team on Addiction, University of Minnesota, Minneapolis, Minnesota 55455
- Department of Neuroscience, University of Minnesota, Minneapolis, Minnesota 55455
| | - Anika Paulson
- Medical Discovery Team on Addiction, University of Minnesota, Minneapolis, Minnesota 55455
- Department of Neuroscience, University of Minnesota, Minneapolis, Minnesota 55455
| | - Paige Remde
- Medical Discovery Team on Addiction, University of Minnesota, Minneapolis, Minnesota 55455
- Department of Neuroscience, University of Minnesota, Minneapolis, Minnesota 55455
| | - Jocelyn M Richard
- Medical Discovery Team on Addiction, University of Minnesota, Minneapolis, Minnesota 55455
- Department of Neuroscience, University of Minnesota, Minneapolis, Minnesota 55455
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27
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Girardi G, Zumpano D, Goshi N, Raybould H, Seker E. Cultured Vagal Afferent Neurons as Sensors for Intestinal Effector Molecules. BIOSENSORS 2023; 13:601. [PMID: 37366967 DOI: 10.3390/bios13060601] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 05/23/2023] [Accepted: 05/24/2023] [Indexed: 06/28/2023]
Abstract
The gut-brain axis embodies the bi-directional communication between the gastrointestinal tract and the central nervous system (CNS), where vagal afferent neurons (VANs) serve as sensors for a variety of gut-derived signals. The gut is colonized by a large and diverse population of microorganisms that communicate via small (effector) molecules, which also act on the VAN terminals situated in the gut viscera and consequently influence many CNS processes. However, the convoluted in vivo environment makes it difficult to study the causative impact of the effector molecules on VAN activation or desensitization. Here, we report on a VAN culture and its proof-of-principle demonstration as a cell-based sensor to monitor the influence of gastrointestinal effector molecules on neuronal behavior. We initially compared the effect of surface coatings (poly-L-lysine vs. Matrigel) and culture media composition (serum vs. growth factor supplement) on neurite growth as a surrogate of VAN regeneration following tissue harvesting, where the Matrigel coating, but not the media composition, played a significant role in the increased neurite growth. We then used both live-cell calcium imaging and extracellular electrophysiological recordings to show that the VANs responded to classical effector molecules of endogenous and exogenous origin (cholecystokinin serotonin and capsaicin) in a complex fashion. We expect this study to enable platforms for screening various effector molecules and their influence on VAN activity, assessed by their information-rich electrophysiological fingerprints.
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Affiliation(s)
- Gregory Girardi
- Department of Biomedical Engineering, University of California-Davis, Davis, CA 95616, USA
| | - Danielle Zumpano
- Department of Anatomy, Physiology and Cell Biology, School of Veterinary Medicine, University of California-Davis, Davis, CA 95616, USA
| | - Noah Goshi
- Department of Biomedical Engineering, University of California-Davis, Davis, CA 95616, USA
| | - Helen Raybould
- Department of Anatomy, Physiology and Cell Biology, School of Veterinary Medicine, University of California-Davis, Davis, CA 95616, USA
| | - Erkin Seker
- Department of Electrical and Computer Engineering, University of California-Davis, Davis, CA 95616, USA
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28
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Ferguson KA, Salameh J, Alba C, Selwyn H, Barnes C, Lohani S, Cardin JA. VIP interneurons regulate cortical size tuning and visual perception. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.14.532664. [PMID: 37162871 PMCID: PMC10168200 DOI: 10.1101/2023.03.14.532664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
Local cortical circuit function is regulated by diverse populations of GABAergic interneurons with distinct properties and extensive interconnectivity. Inhibitory-to-inhibitory interactions between interneuron populations may play key roles in shaping circuit operation according to behavioral context. A specialized population of GABAergic interneurons that co-express vasoactive intestinal peptide (VIP-INs) are activated during arousal and locomotion and innervate other local interneurons and pyramidal neurons. Although modulation of VIP-IN activity by behavioral state has been extensively studied, their role in regulating information processing and selectivity is less well understood. Using a combination of cellular imaging, short and long-term manipulation, and perceptual behavior, we examined the impact of VIP-INs on their synaptic target populations in the primary visual cortex of awake behaving mice. We find that loss of VIP-IN activity alters the behavioral state-dependent modulation of somatostatin-expressing interneurons (SST-INs) but not pyramidal neurons (PNs). In contrast, reduced VIP-IN activity disrupts visual feature selectivity for stimulus size in both populations. Inhibitory-to inhibitory interactions thus directly shape the selectivity of GABAergic interneurons for sensory stimuli. Moreover, the impact of VIP-IN activity on perceptual behavior varies with visual context and is more acute for small than large visual cues. VIP-INs thus contribute to both state-dependent modulation of cortical circuit activity and sensory context-dependent perceptual performance.
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Affiliation(s)
- Katie A Ferguson
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510 USA
| | - Jenna Salameh
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510 USA
| | - Christopher Alba
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510 USA
| | - Hannah Selwyn
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510 USA
| | - Clayton Barnes
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510 USA
| | - Sweyta Lohani
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510 USA
| | - Jessica A Cardin
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510 USA
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29
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Delepine C, Shih J, Li K, Gaudeaux P, Sur M. Differential Effects of Astrocyte Manipulations on Learned Motor Behavior and Neuronal Ensembles in the Motor Cortex. J Neurosci 2023; 43:2696-2713. [PMID: 36894315 PMCID: PMC10089242 DOI: 10.1523/jneurosci.1982-22.2023] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Revised: 01/31/2023] [Accepted: 03/01/2023] [Indexed: 03/11/2023] Open
Abstract
Although motor cortex is crucial for learning precise and reliable movements, whether and how astrocytes contribute to its plasticity and function during motor learning is unknown. Here, we report that astrocyte-specific manipulations in primary motor cortex (M1) during a lever push task alter motor learning and execution, as well as the underlying neuronal population coding. Mice that express decreased levels of the astrocyte glutamate transporter 1 (GLT1) show impaired and variable movement trajectories, whereas mice with increased astrocyte Gq signaling show decreased performance rates, delayed response times, and impaired trajectories. In both groups, which include male and female mice, M1 neurons have altered interneuronal correlations and impaired population representations of task parameters, including response time and movement trajectories. RNA sequencing further supports a role for M1 astrocytes in motor learning and shows changes in astrocytic expression of glutamate transporter genes, GABA transporter genes, and extracellular matrix protein genes in mice that have acquired this learned behavior. Thus, astrocytes coordinate M1 neuronal activity during motor learning, and our results suggest that this contributes to learned movement execution and dexterity through mechanisms that include regulation of neurotransmitter transport and calcium signaling.SIGNIFICANCE STATEMENT We demonstrate for the first time that in the M1 of mice, astrocyte function is critical for coordinating neuronal population activity during motor learning. We demonstrate that knockdown of astrocyte glutamate transporter GLT1 affects specific components of learning, such as smooth trajectory formation. Altering astrocyte calcium signaling by activation of Gq-DREADD upregulates GLT1 and affects other components of learning, such as response rates and reaction times as well as trajectory smoothness. In both manipulations, neuronal activity in motor cortex is dysregulated, but in different ways. Thus, astrocytes have a crucial role in motor learning via their influence on motor cortex neurons, and they do so by mechanisms that include regulation of glutamate transport and calcium signals.
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Affiliation(s)
- Chloe Delepine
- The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
| | - Jennifer Shih
- The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
| | - Keji Li
- The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
| | - Pierre Gaudeaux
- The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
| | - Mriganka Sur
- The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
- Simons Center for the Social Brain, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
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30
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Neuronal Cultures: Exploring Biophysics, Complex Systems, and Medicine in a Dish. BIOPHYSICA 2023. [DOI: 10.3390/biophysica3010012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2023]
Abstract
Neuronal cultures are one of the most important experimental models in modern interdisciplinary neuroscience, allowing to investigate in a control environment the emergence of complex behavior from an ensemble of interconnected neurons. Here, I review the research that we have conducted at the neurophysics laboratory at the University of Barcelona over the last 15 years, describing first the neuronal cultures that we prepare and the associated tools to acquire and analyze data, to next delve into the different research projects in which we actively participated to progress in the understanding of open questions, extend neuroscience research on new paradigms, and advance the treatment of neurological disorders. I finish the review by discussing the drawbacks and limitations of neuronal cultures, particularly in the context of brain-like models and biomedicine.
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31
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DePasquale B, Sussillo D, Abbott LF, Churchland MM. The centrality of population-level factors to network computation is demonstrated by a versatile approach for training spiking networks. Neuron 2023; 111:631-649.e10. [PMID: 36630961 PMCID: PMC10118067 DOI: 10.1016/j.neuron.2022.12.007] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Revised: 06/17/2022] [Accepted: 12/05/2022] [Indexed: 01/12/2023]
Abstract
Neural activity is often described in terms of population-level factors extracted from the responses of many neurons. Factors provide a lower-dimensional description with the aim of shedding light on network computations. Yet, mechanistically, computations are performed not by continuously valued factors but by interactions among neurons that spike discretely and variably. Models provide a means of bridging these levels of description. We developed a general method for training model networks of spiking neurons by leveraging factors extracted from either data or firing-rate-based networks. In addition to providing a useful model-building framework, this formalism illustrates how reliable and continuously valued factors can arise from seemingly stochastic spiking. Our framework establishes procedures for embedding this property in network models with different levels of realism. The relationship between spikes and factors in such networks provides a foundation for interpreting (and subtly redefining) commonly used quantities such as firing rates.
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Affiliation(s)
- Brian DePasquale
- Princeton Neuroscience Institute, Princeton University, Princeton NJ, USA; Department of Neuroscience, Columbia University, New York, NY, USA; Center for Theoretical Neuroscience, Columbia University, New York, NY, USA.
| | - David Sussillo
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA; Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
| | - L F Abbott
- Department of Neuroscience, Columbia University, New York, NY, USA; Center for Theoretical Neuroscience, Columbia University, New York, NY, USA; Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA; Department of Physiology and Cellular Biophysics, Columbia University, New York, NY, USA; Kavli Institute for Brain Science, Columbia University, New York, NY, USA
| | - Mark M Churchland
- Department of Neuroscience, Columbia University, New York, NY, USA; Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA; Kavli Institute for Brain Science, Columbia University, New York, NY, USA; Grossman Center for the Statistics of Mind, Columbia University, New York, NY, USA
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32
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Zhang Y, Rózsa M, Liang Y, Bushey D, Wei Z, Zheng J, Reep D, Broussard GJ, Tsang A, Tsegaye G, Narayan S, Obara CJ, Lim JX, Patel R, Zhang R, Ahrens MB, Turner GC, Wang SSH, Korff WL, Schreiter ER, Svoboda K, Hasseman JP, Kolb I, Looger LL. Fast and sensitive GCaMP calcium indicators for imaging neural populations. Nature 2023; 615:884-891. [PMID: 36922596 PMCID: PMC10060165 DOI: 10.1038/s41586-023-05828-9] [Citation(s) in RCA: 170] [Impact Index Per Article: 170.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Accepted: 02/10/2023] [Indexed: 03/17/2023]
Abstract
Calcium imaging with protein-based indicators1,2 is widely used to follow neural activity in intact nervous systems, but current protein sensors report neural activity at timescales much slower than electrical signalling and are limited by trade-offs between sensitivity and kinetics. Here we used large-scale screening and structure-guided mutagenesis to develop and optimize several fast and sensitive GCaMP-type indicators3-8. The resulting 'jGCaMP8' sensors, based on the calcium-binding protein calmodulin and a fragment of endothelial nitric oxide synthase, have ultra-fast kinetics (half-rise times of 2 ms) and the highest sensitivity for neural activity reported for a protein-based calcium sensor. jGCaMP8 sensors will allow tracking of large populations of neurons on timescales relevant to neural computation.
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Affiliation(s)
- Yan Zhang
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Márton Rózsa
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- Allen Institute for Neural Dynamics, Seattle, WA, USA
| | - Yajie Liang
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- Genetically Encoded Neural Indicator and Effector (GENIE) Project, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Daniel Bushey
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Ziqiang Wei
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Jihong Zheng
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- Genetically Encoded Neural Indicator and Effector (GENIE) Project, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Daniel Reep
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- Genetically Encoded Neural Indicator and Effector (GENIE) Project, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | | | - Arthur Tsang
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- Genetically Encoded Neural Indicator and Effector (GENIE) Project, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Getahun Tsegaye
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- Genetically Encoded Neural Indicator and Effector (GENIE) Project, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Sujatha Narayan
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- Allen Institute for Neural Dynamics, Seattle, WA, USA
| | | | - Jing-Xuan Lim
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Ronak Patel
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Rongwei Zhang
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Misha B Ahrens
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Glenn C Turner
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA.
- Genetically Encoded Neural Indicator and Effector (GENIE) Project, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA.
| | - Samuel S-H Wang
- Neuroscience Institute, Princeton University, Princeton, NJ, USA.
| | - Wyatt L Korff
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- Genetically Encoded Neural Indicator and Effector (GENIE) Project, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Eric R Schreiter
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- Genetically Encoded Neural Indicator and Effector (GENIE) Project, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Karel Svoboda
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA.
- Allen Institute for Neural Dynamics, Seattle, WA, USA.
- Genetically Encoded Neural Indicator and Effector (GENIE) Project, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA.
| | - Jeremy P Hasseman
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA.
- Genetically Encoded Neural Indicator and Effector (GENIE) Project, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA.
| | - Ilya Kolb
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- Genetically Encoded Neural Indicator and Effector (GENIE) Project, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Loren L Looger
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA.
- Genetically Encoded Neural Indicator and Effector (GENIE) Project, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA.
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA.
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33
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Assessing brain state and anesthesia level with two-photon calcium signals. Sci Rep 2023; 13:3183. [PMID: 36823228 PMCID: PMC9950142 DOI: 10.1038/s41598-023-30224-8] [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: 12/07/2022] [Accepted: 02/17/2023] [Indexed: 02/25/2023] Open
Abstract
Brain states, such as wake, sleep, or different depths of anesthesia are usually assessed using electrophysiological techniques, such as the local field potential (LFP) or the electroencephalogram (EEG), which are ideal signals for detecting activity patterns such as asynchronous or oscillatory activities. However, it is technically challenging to have these types of measures during calcium imaging recordings such as two-photon or wide-field techniques. Here, using simultaneous two-photon and LFP measurements, we demonstrate that despite the slower dynamics of the calcium signal, there is a high correlation between the LFP and two-photon signals taken from the neuropil outside neuronal somata. Moreover, we find the calcium signal to be systematically delayed from the LFP signal, and we use a model to show that the delay between the two signals is due to the physical distance between the recording sites. These results suggest that calcium signals alone can be used to detect activity patterns such as slow oscillations and ultimately assess the brain state and level of anesthesia.
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Guo C, Wang A, Cheng H, Chen L. New imaging instrument in animal models: Two-photon miniature microscope and large field of view miniature microscope for freely behaving animals. J Neurochem 2023; 164:270-283. [PMID: 36281555 DOI: 10.1111/jnc.15711] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2022] [Revised: 09/19/2022] [Accepted: 10/12/2022] [Indexed: 11/30/2022]
Abstract
Over the past decade, novel optical imaging tools have been developed for imaging neuronal activities along with the evolution of fluorescence indicators with brighter expression and higher sensitivity. Miniature microscopes, as revolutionary approaches, enable the imaging of large populations of neuron ensembles in freely behaving rodents and mammals, which allows exploring the neural basis of behaviors. Recent progress in two-photon miniature microscopes and mesoscale single-photon miniature microscopes further expand those affordable methods to navigate neural activities during naturalistic behaviors. In this review article, two-photon miniature microscopy techniques are summarized historically from the first documented attempt to the latest ones, and comparisons are made. The driving force behind and their potential for neuroscientific inquiries are also discussed. Current progress in terms of the mesoscale, i.e., the large field-of-view miniature microscopy technique, is addressed as well. Then, pipelines for registering single cells from the data of two-photon and large field-of-view miniature microscopes are discussed. Finally, we present the potential evolution of the techniques.
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Affiliation(s)
- Changliang Guo
- Beijing Institute of Collaborative Innovation, Beijing, China.,State Key Laboratory of Membrane Biology, Institute of Molecular Medicine, Peking-Tsinghua Center for Life Sciences, College of Future Technology, Peking University, Beijing, China
| | - Aimin Wang
- School of Electronics, Peking University, Beijing, China.,State Key Laboratory of Advanced Optical Communication System and Networks, Peking University, Beijing, China
| | - Heping Cheng
- 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, China
| | - Liangyi Chen
- State Key Laboratory of Membrane Biology, Institute of Molecular Medicine, Peking-Tsinghua Center for Life Sciences, College of Future Technology, Peking University, Beijing, China.,PKU-IDG/McGovern Institute for Brain Research, Beijing, China.,Beijing Academy of Artificial Intelligence, Beijing, China
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35
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Day-Cooney J, Dalangin R, Zhong H, Mao T. Genetically encoded fluorescent sensors for imaging neuronal dynamics in vivo. J Neurochem 2023; 164:284-308. [PMID: 35285522 DOI: 10.1111/jnc.15608] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 02/14/2022] [Accepted: 02/25/2022] [Indexed: 11/29/2022]
Abstract
The brain relies on many forms of dynamic activities in individual neurons, from synaptic transmission to electrical activity and intracellular signaling events. Monitoring these neuronal activities with high spatiotemporal resolution in the context of animal behavior is a necessary step to achieve a mechanistic understanding of brain function. With the rapid development and dissemination of highly optimized genetically encoded fluorescent sensors, a growing number of brain activities can now be visualized in vivo. To date, cellular calcium imaging, which has been largely used as a proxy for electrical activity, has become a mainstay in systems neuroscience. While challenges remain, voltage imaging of neural populations is now possible. In addition, it is becoming increasingly practical to image over half a dozen neurotransmitters, as well as certain intracellular signaling and metabolic activities. These new capabilities enable neuroscientists to test previously unattainable hypotheses and questions. This review summarizes recent progress in the development and delivery of genetically encoded fluorescent sensors, and highlights example applications in the context of in vivo imaging.
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Affiliation(s)
- Julian Day-Cooney
- Vollum Institute, Oregon Health and Science University, Portland, Oregon, USA
| | - Rochelin Dalangin
- Department of Biochemistry and Molecular Medicine, University of California, Davis, Davis, California, USA
| | - Haining Zhong
- Vollum Institute, Oregon Health and Science University, Portland, Oregon, USA
| | - Tianyi Mao
- Vollum Institute, Oregon Health and Science University, Portland, Oregon, USA
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36
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Koh TH, Bishop WE, Kawashima T, Jeon BB, Srinivasan R, Mu Y, Wei Z, Kuhlman SJ, Ahrens MB, Chase SM, Yu BM. Dimensionality reduction of calcium-imaged neuronal population activity. NATURE COMPUTATIONAL SCIENCE 2023; 3:71-85. [PMID: 37476302 PMCID: PMC10358781 DOI: 10.1038/s43588-022-00390-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Accepted: 12/05/2022] [Indexed: 07/22/2023]
Abstract
Calcium imaging has been widely adopted for its ability to record from large neuronal populations. To summarize the time course of neural activity, dimensionality reduction methods, which have been applied extensively to population spiking activity, may be particularly useful. However, it is unclear if the dimensionality reduction methods applied to spiking activity are appropriate for calcium imaging. We thus carried out a systematic study of design choices based on standard dimensionality reduction methods. We also developed a method to perform deconvolution and dimensionality reduction simultaneously (Calcium Imaging Linear Dynamical System, CILDS). CILDS most accurately recovered the single-trial, low-dimensional time courses from simulated calcium imaging data. CILDS also outperformed the other methods on calcium imaging recordings from larval zebrafish and mice. More broadly, this study represents a foundation for summarizing calcium imaging recordings of large neuronal populations using dimensionality reduction in diverse experimental settings.
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Affiliation(s)
- Tze Hui Koh
- Department of Biomedical Engineering, Carnegie Mellon University, PA
- Center for the Neural Basis of Cognition, PA
| | - William E. Bishop
- Center for the Neural Basis of Cognition, PA
- Department of Machine Learning, Carnegie Mellon University, PA
- Janelia Research Campus, Howard Hughes Medical Institute, VA
| | - Takashi Kawashima
- Janelia Research Campus, Howard Hughes Medical Institute, VA
- Department of Brain Sciences, Weizmann Institute of Science, Israel
| | - Brian B. Jeon
- Department of Biomedical Engineering, Carnegie Mellon University, PA
- Center for the Neural Basis of Cognition, PA
| | - Ranjani Srinivasan
- Department of Biomedical Engineering, Carnegie Mellon University, PA
- Department of Electrical and Computer Engineering, Johns Hopkins University, MD
| | - Yu Mu
- Institute of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, China
| | - Ziqiang Wei
- Janelia Research Campus, Howard Hughes Medical Institute, VA
| | - Sandra J. Kuhlman
- Carnegie Mellon Neuroscience Institute, Carnegie Mellon University, PA
- Department of Biological Sciences, Carnegie Mellon University, PA
| | - Misha B. Ahrens
- Janelia Research Campus, Howard Hughes Medical Institute, VA
| | - Steven M. Chase
- Department of Biomedical Engineering, Carnegie Mellon University, PA
- Carnegie Mellon Neuroscience Institute, Carnegie Mellon University, PA
| | - Byron M. Yu
- Department of Biomedical Engineering, Carnegie Mellon University, PA
- Carnegie Mellon Neuroscience Institute, Carnegie Mellon University, PA
- Department of Electrical and Computer Engineering, Carnegie Mellon University, PA
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37
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Hart EE, Gardner MPH, Panayi MC, Kahnt T, Schoenbaum G. Calcium activity is a degraded estimate of spikes. Curr Biol 2022; 32:5364-5373.e4. [PMID: 36368324 PMCID: PMC9772124 DOI: 10.1016/j.cub.2022.10.037] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 09/20/2022] [Accepted: 10/18/2022] [Indexed: 11/12/2022]
Abstract
Recording action potentials extracellularly during behavior has led to fundamental discoveries regarding neural function-hippocampal neurons respond to locations in space,1 motor cortex neurons encode movement direction,2 and dopamine neurons signal reward prediction errors3-observations undergirding current theories of cognition,4 movement,5 and learning.6 Recently it has become possible to measure calcium flux, an internal cellular signal related to spiking. The ability to image calcium flux in anatomically7,8 or genetically9 identified neurons can extend our knowledge of neural circuit function by allowing activity to be monitored in specific cell types or projections, or in the same neurons across many days. However, while initial studies were grounded in prior unit recording work, it has become fashionable to assume that calcium is identical to spiking, even though the spike-to-fluorescence transformation is nonlinear, noisy, and unpredictable under real-world conditions.10 It remains an open question whether calcium provides a high-fidelity representation of single-unit activity in awake, behaving subjects. Here, we have addressed this question by recording both signals in the lateral orbitofrontal cortex (OFC) of rats during olfactory discrimination learning. Activity in the OFC during olfactory learning has been well-studied in humans,11,12,13,14 nonhuman primates,15,16 and rats,17,18,19,20,21 where it has been shown to signal information about both the sensory properties of odor cues and the rewards they predict. Our single-unit results replicated prior findings, whereas the calcium signal provided only a degraded estimate of the information available in the single-unit spiking, reflecting primarily reward value.
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Affiliation(s)
- Evan E Hart
- National Institute on Drug Abuse Intramural Research Program, 251 Bayview Boulevard, Baltimore, MD 21224, USA
- National Institute of General Medical Sciences, 45 Center Drive, Bethesda, MD 20892, USA
| | - Matthew PH Gardner
- National Institute on Drug Abuse Intramural Research Program, 251 Bayview Boulevard, Baltimore, MD 21224, USA
- Department of Psychology, Concordia University, 7141 Sherbrooke West, Montreal, QC H4B 1R6, CA
| | - Marios C Panayi
- National Institute on Drug Abuse Intramural Research Program, 251 Bayview Boulevard, Baltimore, MD 21224, USA
| | - Thorsten Kahnt
- National Institute on Drug Abuse Intramural Research Program, 251 Bayview Boulevard, Baltimore, MD 21224, USA
| | - Geoffrey Schoenbaum
- National Institute on Drug Abuse Intramural Research Program, 251 Bayview Boulevard, Baltimore, MD 21224, USA
- Department of Anatomy and Neurobiology, University of Maryland School of Medicine, 110 S Paca Street, Baltimore, MD 21201, USA
- Department of Neuroscience, Johns Hopkins School of Medicine, 251 Bayview Boulevard, Baltimore, MD 21224, USA
- Department of Psychiatry, University of Maryland School of Medicine, 110 S Paca Street, Baltimore, MD 21201, USA
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38
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Celotto M, Lemke S, Panzeri S. Inferring the temporal evolution of synaptic weights from dynamic functional connectivity. Brain Inform 2022; 9:28. [PMID: 36480076 PMCID: PMC9732068 DOI: 10.1186/s40708-022-00178-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Accepted: 11/14/2022] [Indexed: 12/13/2022] Open
Abstract
How to capture the temporal evolution of synaptic weights from measures of dynamic functional connectivity between the activity of different simultaneously recorded neurons is an important and open problem in systems neuroscience. Here, we report methodological progress to address this issue. We first simulated recurrent neural network models of spiking neurons with spike timing-dependent plasticity mechanisms that generate time-varying synaptic and functional coupling. We then used these simulations to test analytical approaches that infer fixed and time-varying properties of synaptic connectivity from directed functional connectivity measures, such as cross-covariance and transfer entropy. We found that, while both cross-covariance and transfer entropy provide robust estimates of which synapses are present in the network and their communication delays, dynamic functional connectivity measured via cross-covariance better captures the evolution of synaptic weights over time. We also established how measures of information transmission delays from static functional connectivity computed over long recording periods (i.e., several hours) can improve shorter time-scale estimates of the temporal evolution of synaptic weights from dynamic functional connectivity. These results provide useful information about how to accurately estimate the temporal variation of synaptic strength from spiking activity measures.
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Affiliation(s)
- Marco Celotto
- grid.13648.380000 0001 2180 3484Department of Excellence for Neural Information Processing, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany ,grid.25786.3e0000 0004 1764 2907Neural Computation Laboratory, Istituto Italiano di Tecnologia, Rovereto, Italy ,grid.6292.f0000 0004 1757 1758Department of Pharmacy and Biotechnology, University of Bologna, Bologna, Italy
| | - Stefan Lemke
- grid.25786.3e0000 0004 1764 2907Neural Computation Laboratory, Istituto Italiano di Tecnologia, Rovereto, Italy ,grid.410711.20000 0001 1034 1720Department of Cell Biology and Physiology, University of North Carolina, Chapel Hill, USA
| | - Stefano Panzeri
- grid.13648.380000 0001 2180 3484Department of Excellence for Neural Information Processing, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany ,grid.25786.3e0000 0004 1764 2907Neural Computation Laboratory, Istituto Italiano di Tecnologia, Rovereto, Italy
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39
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Zhu F, Grier HA, Tandon R, Cai C, Agarwal A, Giovannucci A, Kaufman MT, Pandarinath C. A deep learning framework for inference of single-trial neural population dynamics from calcium imaging with subframe temporal resolution. Nat Neurosci 2022; 25:1724-1734. [PMID: 36424431 PMCID: PMC9825112 DOI: 10.1038/s41593-022-01189-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Accepted: 09/23/2022] [Indexed: 11/26/2022]
Abstract
In many areas of the brain, neural populations act as a coordinated network whose state is tied to behavior on a millisecond timescale. Two-photon (2p) calcium imaging is a powerful tool to probe such network-scale phenomena. However, estimating the network state and dynamics from 2p measurements has proven challenging because of noise, inherent nonlinearities and limitations on temporal resolution. Here we describe Recurrent Autoencoder for Discovering Imaged Calcium Latents (RADICaL), a deep learning method to overcome these limitations at the population level. RADICaL extends methods that exploit dynamics in spiking activity for application to deconvolved calcium signals, whose statistics and temporal dynamics are quite distinct from electrophysiologically recorded spikes. It incorporates a new network training strategy that capitalizes on the timing of 2p sampling to recover network dynamics with high temporal precision. In synthetic tests, RADICaL infers the network state more accurately than previous methods, particularly for high-frequency components. In 2p recordings from sensorimotor areas in mice performing a forelimb reach task, RADICaL infers network state with close correspondence to single-trial variations in behavior and maintains high-quality inference even when neuronal populations are substantially reduced.
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Affiliation(s)
- Feng Zhu
- Wallace H. Coulter Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA, USA
- Neuroscience Graduate Program, Graduate Division of Biological and Biomedical Sciences, Emory University, Atlanta, GA, USA
| | - Harrison A Grier
- Committee on Computational Neuroscience, The University of Chicago, Chicago, IL, USA
| | - Raghav Tandon
- Wallace H. Coulter Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA, USA
| | - Changjia Cai
- Joint Biomedical Engineering Department, University of North Carolina at Chapel Hill and North Carolina State University, Chapel Hill, NC, USA
| | | | - Andrea Giovannucci
- Joint Biomedical Engineering Department, University of North Carolina at Chapel Hill and North Carolina State University, Chapel Hill, NC, USA.
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
- Closed-Loop Engineering for Advanced Rehabilitation (CLEAR), North Carolina State University, Raleigh, NC, USA.
| | - Matthew T Kaufman
- Department of Organismal Biology and Anatomy, The University of Chicago, Chicago, IL, USA.
- Neuroscience Institute, The University of Chicago, Chicago, IL, USA.
| | - Chethan Pandarinath
- Wallace H. Coulter Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA, USA.
- Department of Neurosurgery, Emory University, Atlanta, GA, USA.
- Center for Machine Learning, Georgia Institute of Technology, Atlanta, GA, USA.
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40
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Chiappalone M, Cota VR, Carè M, Di Florio M, Beaubois R, Buccelli S, Barban F, Brofiga M, Averna A, Bonacini F, Guggenmos DJ, Bornat Y, Massobrio P, Bonifazi P, Levi T. Neuromorphic-Based Neuroprostheses for Brain Rewiring: State-of-the-Art and Perspectives in Neuroengineering. Brain Sci 2022; 12:1578. [PMID: 36421904 PMCID: PMC9688667 DOI: 10.3390/brainsci12111578] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 11/09/2022] [Accepted: 11/17/2022] [Indexed: 08/27/2023] Open
Abstract
Neuroprostheses are neuroengineering devices that have an interface with the nervous system and supplement or substitute functionality in people with disabilities. In the collective imagination, neuroprostheses are mostly used to restore sensory or motor capabilities, but in recent years, new devices directly acting at the brain level have been proposed. In order to design the next-generation of neuroprosthetic devices for brain repair, we foresee the increasing exploitation of closed-loop systems enabled with neuromorphic elements due to their intrinsic energy efficiency, their capability to perform real-time data processing, and of mimicking neurobiological computation for an improved synergy between the technological and biological counterparts. In this manuscript, after providing definitions of key concepts, we reviewed the first exploitation of a real-time hardware neuromorphic prosthesis to restore the bidirectional communication between two neuronal populations in vitro. Starting from that 'case-study', we provide perspectives on the technological improvements for real-time interfacing and processing of neural signals and their potential usage for novel in vitro and in vivo experimental designs. The development of innovative neuroprosthetics for translational purposes is also presented and discussed. In our understanding, the pursuit of neuromorphic-based closed-loop neuroprostheses may spur the development of novel powerful technologies, such as 'brain-prostheses', capable of rewiring and/or substituting the injured nervous system.
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Affiliation(s)
- Michela Chiappalone
- Department of Informatics, Bioengineering, Robotics System Engineering (DIBRIS), University of Genova, 16145 Genova, Italy
- Rehab Technologies, Istituto Italiano di Tecnologia, 16163 Genova, Italy
| | - Vinicius R. Cota
- Rehab Technologies, Istituto Italiano di Tecnologia, 16163 Genova, Italy
| | - Marta Carè
- Department of Informatics, Bioengineering, Robotics System Engineering (DIBRIS), University of Genova, 16145 Genova, Italy
- Rehab Technologies, Istituto Italiano di Tecnologia, 16163 Genova, Italy
| | - Mattia Di Florio
- Department of Informatics, Bioengineering, Robotics System Engineering (DIBRIS), University of Genova, 16145 Genova, Italy
| | - Romain Beaubois
- IMS Laboratory, CNRS UMR 5218, University of Bordeaux, 33405 Talence, France
| | - Stefano Buccelli
- Rehab Technologies, Istituto Italiano di Tecnologia, 16163 Genova, Italy
| | - Federico Barban
- Department of Informatics, Bioengineering, Robotics System Engineering (DIBRIS), University of Genova, 16145 Genova, Italy
- Rehab Technologies, Istituto Italiano di Tecnologia, 16163 Genova, Italy
| | - Martina Brofiga
- Department of Informatics, Bioengineering, Robotics System Engineering (DIBRIS), University of Genova, 16145 Genova, Italy
| | - Alberto Averna
- Department of Neurology, Bern University Hospital, University of Bern, 3012 Bern, Switzerland
| | - Francesco Bonacini
- Department of Informatics, Bioengineering, Robotics System Engineering (DIBRIS), University of Genova, 16145 Genova, Italy
| | - David J. Guggenmos
- Department of Rehabilitation Medicine, University of Kansas Medical Center, Kansas City, KS 66103, USA
- Landon Center on Aging, University of Kansas Medical Center, Kansas City, KS 66103, USA
| | - Yannick Bornat
- IMS Laboratory, CNRS UMR 5218, University of Bordeaux, 33405 Talence, France
| | - Paolo Massobrio
- Department of Informatics, Bioengineering, Robotics System Engineering (DIBRIS), University of Genova, 16145 Genova, Italy
- National Institute for Nuclear Physics (INFN), 16146 Genova, Italy
| | - Paolo Bonifazi
- IKERBASQUE, The Basque Fundation, 48009 Bilbao, Spain
- Biocruces Health Research Institute, 48903 Barakaldo, Spain
| | - Timothée Levi
- IMS Laboratory, CNRS UMR 5218, University of Bordeaux, 33405 Talence, France
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41
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Machado TA, Kauvar IV, Deisseroth K. Multiregion neuronal activity: the forest and the trees. Nat Rev Neurosci 2022; 23:683-704. [PMID: 36192596 PMCID: PMC10327445 DOI: 10.1038/s41583-022-00634-0] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/25/2022] [Indexed: 12/12/2022]
Abstract
The past decade has witnessed remarkable advances in the simultaneous measurement of neuronal activity across many brain regions, enabling fundamentally new explorations of the brain-spanning cellular dynamics that underlie sensation, cognition and action. These recently developed multiregion recording techniques have provided many experimental opportunities, but thoughtful consideration of methodological trade-offs is necessary, especially regarding field of view, temporal acquisition rate and ability to guarantee cellular resolution. When applied in concert with modern optogenetic and computational tools, multiregion recording has already made possible fundamental biological discoveries - in part via the unprecedented ability to perform unbiased neural activity screens for principles of brain function, spanning dozens of brain areas and from local to global scales.
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Affiliation(s)
- Timothy A Machado
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Isaac V Kauvar
- Department of Bioengineering, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Karl Deisseroth
- Department of Bioengineering, 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.
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42
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Post RJ, Bulkin DA, Ebitz RB, Lee V, Han K, Warden MR. Tonic activity in lateral habenula neurons acts as a neutral valence brake on reward-seeking behavior. Curr Biol 2022; 32:4325-4336.e5. [PMID: 36049479 PMCID: PMC9613558 DOI: 10.1016/j.cub.2022.08.016] [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: 01/25/2021] [Revised: 12/16/2021] [Accepted: 08/09/2022] [Indexed: 11/16/2022]
Abstract
Survival requires both the ability to persistently pursue goals and the ability to determine when it is time to stop, an adaptive balance of perseverance and disengagement. Neural activity in the lateral habenula (LHb) has been linked to negative valence, but its role in regulating the balance between engaged reward seeking and disengaged behavioral states remains unclear. Here, we show that LHb neural activity is tonically elevated during minutes-long periods of disengagement from reward-seeking behavior, both when due to repeated reward omission (negative valence) and when sufficient reward has been consumed (positive valence). Furthermore, we show that LHb inhibition extends ongoing reward-seeking behavioral states but does not prompt task re-engagement. We find no evidence for similar tonic activity changes in ventral tegmental area dopamine neurons. Our findings support a framework in which tonic activity in LHb neurons suppresses engagement in reward-seeking behavior in response to both negatively and positively valenced factors.
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Affiliation(s)
- Ryan J Post
- Department of Neurobiology and Behavior, Cornell University, Ithaca, NY 14853, USA; Cornell Neurotech, Cornell University, Ithaca, NY 14853, USA
| | - David A Bulkin
- Department of Neurobiology and Behavior, Cornell University, Ithaca, NY 14853, USA; Cornell Neurotech, Cornell University, Ithaca, NY 14853, USA
| | - R Becket Ebitz
- Department of Neuroscience, Université de Montréal, Montréal, QC H3T 1J4, Canada
| | - Vladlena Lee
- Department of Neurobiology and Behavior, Cornell University, Ithaca, NY 14853, USA
| | - Kasey Han
- Department of Neurobiology and Behavior, Cornell University, Ithaca, NY 14853, USA
| | - Melissa R Warden
- Department of Neurobiology and Behavior, Cornell University, Ithaca, NY 14853, USA; Cornell Neurotech, Cornell University, Ithaca, NY 14853, USA.
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43
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Carrillo-Reid L, Calderon V. Conceptual framework for neuronal ensemble identification and manipulation related to behavior using calcium imaging. NEUROPHOTONICS 2022; 9:041403. [PMID: 35898958 PMCID: PMC9309498 DOI: 10.1117/1.nph.9.4.041403] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Accepted: 07/12/2022] [Indexed: 06/15/2023]
Abstract
Significance: The identification and manipulation of spatially identified neuronal ensembles with optical methods have been recently used to prove the causal link between neuronal ensemble activity and learned behaviors. However, the standardization of a conceptual framework to identify and manipulate neuronal ensembles from calcium imaging recordings is still lacking. Aim: We propose a conceptual framework for the identification and manipulation of neuronal ensembles using simultaneous calcium imaging and two-photon optogenetics in behaving mice. Approach: We review the computational approaches that have been used to identify and manipulate neuronal ensembles with single cell resolution during behavior in different brain regions using all-optical methods. Results: We proposed three steps as a conceptual framework that could be applied to calcium imaging recordings to identify and manipulate neuronal ensembles in behaving mice: (1) transformation of calcium transients into binary arrays; (2) identification of neuronal ensembles as similar population vectors; and (3) targeting of neuronal ensemble members that significantly impact behavioral performance. Conclusions: The use of simultaneous two-photon calcium imaging and two-photon optogenetics allowed for the experimental demonstration of the causal relation of population activity and learned behaviors. The standardization of analytical tools to identify and manipulate neuronal ensembles could accelerate interventional experiments aiming to reprogram the brain in normal and pathological conditions.
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Affiliation(s)
- Luis Carrillo-Reid
- National Autonomous University of Mexico, Neurobiology Institute, Department of Developmental Neurobiology and Neurophysiology, Querétaro, Mexico
| | - Vladimir Calderon
- National Autonomous University of Mexico, Neurobiology Institute, Department of Developmental Neurobiology and Neurophysiology, Querétaro, Mexico
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44
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Zhang YJ, Yu ZF, Liu JK, Huang TJ. Neural Decoding of Visual Information Across Different Neural Recording Modalities and Approaches. MACHINE INTELLIGENCE RESEARCH 2022. [PMCID: PMC9283560 DOI: 10.1007/s11633-022-1335-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Vision plays a peculiar role in intelligence. Visual information, forming a large part of the sensory information, is fed into the human brain to formulate various types of cognition and behaviours that make humans become intelligent agents. Recent advances have led to the development of brain-inspired algorithms and models for machine vision. One of the key components of these methods is the utilization of the computational principles underlying biological neurons. Additionally, advanced experimental neuroscience techniques have generated different types of neural signals that carry essential visual information. Thus, there is a high demand for mapping out functional models for reading out visual information from neural signals. Here, we briefly review recent progress on this issue with a focus on how machine learning techniques can help in the development of models for contending various types of neural signals, from fine-scale neural spikes and single-cell calcium imaging to coarse-scale electroencephalography (EEG) and functional magnetic resonance imaging recordings of brain signals.
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45
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Benisty H, Song A, Mishne G, Charles AS. Review of data processing of functional optical microscopy for neuroscience. NEUROPHOTONICS 2022; 9:041402. [PMID: 35937186 PMCID: PMC9351186 DOI: 10.1117/1.nph.9.4.041402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Accepted: 07/15/2022] [Indexed: 05/04/2023]
Abstract
Functional optical imaging in neuroscience is rapidly growing with the development of optical systems and fluorescence indicators. To realize the potential of these massive spatiotemporal datasets for relating neuronal activity to behavior and stimuli and uncovering local circuits in the brain, accurate automated processing is increasingly essential. We cover recent computational developments in the full data processing pipeline of functional optical microscopy for neuroscience data and discuss ongoing and emerging challenges.
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Affiliation(s)
- Hadas Benisty
- Yale Neuroscience, New Haven, Connecticut, United States
| | - Alexander Song
- Max Planck Institute for Intelligent Systems, Stuttgart, Germany
| | - Gal Mishne
- UC San Diego, Halıcığlu Data Science Institute, Department of Electrical and Computer Engineering and the Neurosciences Graduate Program, La Jolla, California, United States
| | - Adam S. Charles
- Johns Hopkins University, Kavli Neuroscience Discovery Institute, Center for Imaging Science, Department of Biomedical Engineering, Department of Neuroscience, and Mathematical Institute for Data Science, Baltimore, Maryland, United States
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46
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Warm D, Bassetti D, Schroer J, Luhmann HJ, Sinning A. Spontaneous Activity Predicts Survival of Developing Cortical Neurons. Front Cell Dev Biol 2022; 10:937761. [PMID: 36035995 PMCID: PMC9399774 DOI: 10.3389/fcell.2022.937761] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Accepted: 06/20/2022] [Indexed: 11/13/2022] Open
Abstract
Spontaneous activity plays a crucial role in brain development by coordinating the integration of immature neurons into emerging cortical networks. High levels and complex patterns of spontaneous activity are generally associated with low rates of apoptosis in the cortex. However, whether spontaneous activity patterns directly encode for survival of individual cortical neurons during development remains an open question. Here, we longitudinally investigated spontaneous activity and apoptosis in developing cortical cultures, combining extracellular electrophysiology with calcium imaging. These experiments demonstrated that the early occurrence of calcium transients was strongly linked to neuronal survival. Silent neurons exhibited a higher probability of cell death, whereas high frequency spiking and burst behavior were almost exclusively detected in surviving neurons. In local neuronal clusters, activity of neighboring neurons exerted a pro-survival effect, whereas on the functional level, networks with a high modular topology were associated with lower cell death rates. Using machine learning algorithms, cell fate of individual neurons was predictable through the integration of spontaneous activity features. Our results indicate that high frequency spiking activity constrains apoptosis in single neurons through sustained calcium rises and thereby consolidates networks in which a high modular topology is reached during early development.
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47
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Pan Y, Shi LZ, Yoon CW, Preece D, Gomez‐Godinez V, Lu S, Carmona C, Woo S, Chien S, Berns MW, Liu L, Wang Y. Mechanosensor Piezo1 mediates bimodal patterns of intracellular calcium and FAK signaling. EMBO J 2022; 41:e111799. [PMID: 35844093 PMCID: PMC9433934 DOI: 10.15252/embj.2022111799] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Revised: 06/19/2022] [Accepted: 06/28/2022] [Indexed: 01/18/2023] Open
Abstract
Piezo1 belongs to mechano-activatable cation channels serving as biological force sensors. However, the molecular events downstream of Piezo1 activation remain unclear. In this study, we used biosensors based on fluorescence resonance energy transfer (FRET) to investigate the dynamic modes of Piezo1-mediated signaling and revealed a bimodal pattern of Piezo1-induced intracellular calcium signaling. Laser-induced shockwaves (LIS) and its associated shear stress can mechanically activate Piezo1 to induce transient intracellular calcium (Ca[i] ) elevation, accompanied by an increase in FAK activity. Interestingly, multiple pulses of shockwave stimulation caused a more sustained calcium increase and a decrease in FAK activity. Similarly, tuning the degree of Piezo1 activation by titrating either the dosage of Piezo1 ligand Yoda1 or the expression level of Piezo1 produced a similar bimodal pattern of FAK responses. Further investigations revealed that SHP2 serves as an intermediate regulator mediating this bimodal pattern in Piezo1 sensing and signaling. These results suggest that the degrees of Piezo1 activation induced by both mechanical LIS and chemical ligand stimulation may determine downstream signaling characteristics.
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Affiliation(s)
- Yijia Pan
- Department of BioengineeringUniversity of California, San DiegoLa JollaCAUSA
| | - Linda Zhixia Shi
- Institute of Engineering in MedicineUniversity of California, San DiegoLa JollaCAUSA
| | - Chi Woo Yoon
- Department of BioengineeringUniversity of California, San DiegoLa JollaCAUSA
| | - Daryl Preece
- Institute of Engineering in MedicineUniversity of California, San DiegoLa JollaCAUSA
| | | | - Shaoying Lu
- Department of BioengineeringUniversity of California, San DiegoLa JollaCAUSA
| | - Christopher Carmona
- Department of BioengineeringUniversity of California, San DiegoLa JollaCAUSA
| | - Seung‐Hyun Woo
- Department of Cell Biology, Dorris Neuroscience CenterThe Scripps Research InstituteLa JollaCAUSA,Genomic Institute of the Novartis Research FoundationSan DiegoCAUSA
| | - Shu Chien
- Department of BioengineeringUniversity of California, San DiegoLa JollaCAUSA,Institute of Engineering in MedicineUniversity of California, San DiegoLa JollaCAUSA,Department of MedicineUniversity of California, San DiegoLa JollaCAUSA
| | - Michael W Berns
- Institute of Engineering in MedicineUniversity of California, San DiegoLa JollaCAUSA,Beckman Laser Institute and Medical ClinicUniversity of California, IrvineIrvineCAUSA
| | - Longwei Liu
- Department of BioengineeringUniversity of California, San DiegoLa JollaCAUSA,Institute of Engineering in MedicineUniversity of California, San DiegoLa JollaCAUSA
| | - Yingxiao Wang
- Department of BioengineeringUniversity of California, San DiegoLa JollaCAUSA,Institute of Engineering in MedicineUniversity of California, San DiegoLa JollaCAUSA
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48
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Mahadevan A, Codadu NK, Parrish RR. Xenon LFP Analysis Platform Is a Novel Graphical User Interface for Analysis of Local Field Potential From Large-Scale MEA Recordings. Front Neurosci 2022; 16:904931. [PMID: 35844228 PMCID: PMC9285004 DOI: 10.3389/fnins.2022.904931] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2022] [Accepted: 06/08/2022] [Indexed: 11/24/2022] Open
Abstract
High-density multi-electrode array (HD-MEA) has enabled neuronal measurements at high spatial resolution to record local field potentials (LFP), extracellular action potentials, and network-wide extracellular recording on an extended spatial scale. While we have advanced recording systems with over 4,000 electrodes capable of recording data at over 20 kHz, it still presents computational challenges to handle, process, extract, and view information from these large recordings. We have created a computational method, and an open-source toolkit built in Python, rendered on a web browser using Plotly’s Dash for extracting and viewing the data and creating interactive visualization. In addition to extracting and viewing entire or small chunks of data sampled at lower or higher frequencies, respectively, it provides a framework to collect user inputs, analyze channel groups, generate raster plots, view quick summary measures for LFP activity, detect and isolate noise channels, and generate plots and visualization in both time and frequency domain. Incorporated into our Graphical User Interface (GUI), we also created a novel seizure detection method, which can be used to detect the onset of seizures in all or a selected group of channels and provide the following measures of seizures: distance, duration, and propagation across the region of interest. We demonstrate the utility of this toolkit, using datasets collected from an HD-MEA device comprising of 4,096 recording electrodes. For the current analysis, we demonstrate the toolkit and methods with a low sampling frequency dataset (300 Hz) and a group of approximately 400 channels. Using this toolkit, we present novel data demonstrating increased seizure propagation speed from brain slices of Scn1aHet mice compared to littermate controls. While there have been advances in HD-MEA recording systems with high spatial and temporal resolution, limited tools are available for researchers to view and process these big datasets. We now provide a user-friendly toolkit to analyze LFP activity obtained from large-scale MEA recordings with translatable applications to EEG recordings and demonstrate the utility of this new graphic user interface with novel biological findings.
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Affiliation(s)
- Arjun Mahadevan
- Department of Cellular and Molecular Biology, Xenon Pharmaceuticals Inc., Burnaby, BC, Canada
| | - Neela K. Codadu
- Department of Clinical and Experimental Epilepsy, Institute of Neurology, University College London, London, United Kingdom
| | - R. Ryley Parrish
- Department of Cellular and Molecular Biology, Xenon Pharmaceuticals Inc., Burnaby, BC, Canada
- *Correspondence: R. Ryley Parrish,
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49
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A hybrid autoencoder framework of dimensionality reduction for brain-computer interface decoding. Comput Biol Med 2022; 148:105871. [DOI: 10.1016/j.compbiomed.2022.105871] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 06/20/2022] [Accepted: 07/09/2022] [Indexed: 11/19/2022]
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50
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Pedrosa R, Song C, Knöpfel T, Battaglia F. Combining Cortical Voltage Imaging and Hippocampal Electrophysiology for Investigating Global, Multi-Timescale Activity Interactions in the Brain. Int J Mol Sci 2022; 23:ijms23126814. [PMID: 35743257 PMCID: PMC9224488 DOI: 10.3390/ijms23126814] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 06/14/2022] [Accepted: 06/16/2022] [Indexed: 11/17/2022] Open
Abstract
A new generation of optogenetic tools for analyzing neural activity has been contributing to the elucidation of classical open questions in neuroscience. Specifically, voltage imaging technologies using enhanced genetically encoded voltage indicators have been increasingly used to observe the dynamics of large circuits at the mesoscale. Here, we describe how to combine cortical wide-field voltage imaging with hippocampal electrophysiology in awake, behaving mice. Furthermore, we highlight how this method can be useful for different possible investigations, using the characterization of hippocampal–neocortical interactions as a case study.
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Affiliation(s)
- Rafael Pedrosa
- Donders Institute for Brain Cognition and Behaviour, Radboud University, 6525AJ Nijmegen, The Netherlands;
- Correspondence: (R.P.); (T.K.)
| | - Chenchen Song
- Laboratory for Neuronal Circuit Dynamics, Imperial College London, London W12 0NN, UK;
| | - Thomas Knöpfel
- Laboratory for Neuronal Circuit Dynamics, Imperial College London, London W12 0NN, UK;
- Correspondence: (R.P.); (T.K.)
| | - Francesco Battaglia
- Donders Institute for Brain Cognition and Behaviour, Radboud University, 6525AJ Nijmegen, The Netherlands;
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