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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 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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2
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Liu X, Zhang Y, Zhao Y, Zhang Q, Han F. The Neurovascular Unit Dysfunction in the Molecular Mechanisms of Epileptogenesis and Targeted Therapy. Neurosci Bull 2024; 40:621-634. [PMID: 38564049 PMCID: PMC11127907 DOI: 10.1007/s12264-024-01193-3] [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: 08/04/2023] [Accepted: 12/09/2023] [Indexed: 04/04/2024] Open
Abstract
Epilepsy is a multifaceted neurological syndrome characterized by recurrent, spontaneous, and synchronous seizures. The pathogenesis of epilepsy, known as epileptogenesis, involves intricate changes in neurons, neuroglia, and endothelium, leading to structural and functional disorders within neurovascular units and culminating in the development of spontaneous epilepsy. Although current research on epilepsy treatments primarily centers around anti-seizure drugs, it is imperative to seek effective interventions capable of disrupting epileptogenesis. To this end, a comprehensive exploration of the changes and the molecular mechanisms underlying epileptogenesis holds the promise of identifying vital biomarkers for accurate diagnosis and potential therapeutic targets. Emphasizing early diagnosis and timely intervention is paramount, as it stands to significantly improve patient prognosis and alleviate the socioeconomic burden. In this review, we highlight the changes and molecular mechanisms of the neurovascular unit in epileptogenesis and provide a theoretical basis for identifying biomarkers and drug targets.
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Affiliation(s)
- Xiuxiu Liu
- Medical Basic Research Innovation Center for Cardiovascular and Cerebrovascular Diseases, Ministry of Education, Nanjing, 211166, China.
- International Joint Laboratory for Drug Target of Critical Illnesses, School of Pharmacy, Nanjing Medical University, Nanjing, 211166, China.
| | - Ying Zhang
- Medical Basic Research Innovation Center for Cardiovascular and Cerebrovascular Diseases, Ministry of Education, Nanjing, 211166, China
- International Joint Laboratory for Drug Target of Critical Illnesses, School of Pharmacy, Nanjing Medical University, Nanjing, 211166, China
| | - Yanming Zhao
- Medical Basic Research Innovation Center for Cardiovascular and Cerebrovascular Diseases, Ministry of Education, Nanjing, 211166, China
- International Joint Laboratory for Drug Target of Critical Illnesses, School of Pharmacy, Nanjing Medical University, Nanjing, 211166, China
| | - Qian Zhang
- Medical Basic Research Innovation Center for Cardiovascular and Cerebrovascular Diseases, Ministry of Education, Nanjing, 211166, China
- International Joint Laboratory for Drug Target of Critical Illnesses, School of Pharmacy, Nanjing Medical University, Nanjing, 211166, China
| | - Feng Han
- Medical Basic Research Innovation Center for Cardiovascular and Cerebrovascular Diseases, Ministry of Education, Nanjing, 211166, China.
- International Joint Laboratory for Drug Target of Critical Illnesses, School of Pharmacy, Nanjing Medical University, Nanjing, 211166, China.
- Institute of Brain Science, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 211166, China.
- Gusu School, Nanjing Medical University, Suzhou Municipal Hospital, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, 210019, China.
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3
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Gast R, Solla SA, Kennedy A. Neural heterogeneity controls computations in spiking neural networks. Proc Natl Acad Sci U S A 2024; 121:e2311885121. [PMID: 38198531 PMCID: PMC10801870 DOI: 10.1073/pnas.2311885121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Accepted: 11/27/2023] [Indexed: 01/12/2024] Open
Abstract
The brain is composed of complex networks of interacting neurons that express considerable heterogeneity in their physiology and spiking characteristics. How does this neural heterogeneity influence macroscopic neural dynamics, and how might it contribute to neural computation? In this work, we use a mean-field model to investigate computation in heterogeneous neural networks, by studying how the heterogeneity of cell spiking thresholds affects three key computational functions of a neural population: the gating, encoding, and decoding of neural signals. Our results suggest that heterogeneity serves different computational functions in different cell types. In inhibitory interneurons, varying the degree of spike threshold heterogeneity allows them to gate the propagation of neural signals in a reciprocally coupled excitatory population. Whereas homogeneous interneurons impose synchronized dynamics that narrow the dynamic repertoire of the excitatory neurons, heterogeneous interneurons act as an inhibitory offset while preserving excitatory neuron function. Spike threshold heterogeneity also controls the entrainment properties of neural networks to periodic input, thus affecting the temporal gating of synaptic inputs. Among excitatory neurons, heterogeneity increases the dimensionality of neural dynamics, improving the network's capacity to perform decoding tasks. Conversely, homogeneous networks suffer in their capacity for function generation, but excel at encoding signals via multistable dynamic regimes. Drawing from these findings, we propose intra-cell-type heterogeneity as a mechanism for sculpting the computational properties of local circuits of excitatory and inhibitory spiking neurons, permitting the same canonical microcircuit to be tuned for diverse computational tasks.
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Affiliation(s)
- Richard Gast
- Department of Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago, IL60611
- Aligning Science Across Parkinson’s Collaborative Research Network, Chevy Chase, MD20815
| | - Sara A. Solla
- Department of Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago, IL60611
| | - Ann Kennedy
- Department of Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago, IL60611
- Aligning Science Across Parkinson’s Collaborative Research Network, Chevy Chase, MD20815
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4
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Hutt A, Trotter D, Pariz A, Valiante TA, Lefebvre J. Diversity-induced trivialization and resilience of neural dynamics. CHAOS (WOODBURY, N.Y.) 2024; 34:013147. [PMID: 38285722 DOI: 10.1063/5.0165773] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 01/01/2024] [Indexed: 01/31/2024]
Abstract
Heterogeneity is omnipresent across all living systems. Diversity enriches the dynamical repertoire of these systems but remains challenging to reconcile with their manifest robustness and dynamical persistence over time, a fundamental feature called resilience. To better understand the mechanism underlying resilience in neural circuits, we considered a nonlinear network model, extracting the relationship between excitability heterogeneity and resilience. To measure resilience, we quantified the number of stationary states of this network, and how they are affected by various control parameters. We analyzed both analytically and numerically gradient and non-gradient systems modeled as non-linear sparse neural networks evolving over long time scales. Our analysis shows that neuronal heterogeneity quenches the number of stationary states while decreasing the susceptibility to bifurcations: a phenomenon known as trivialization. Heterogeneity was found to implement a homeostatic control mechanism enhancing network resilience to changes in network size and connection probability by quenching the system's dynamic volatility.
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Affiliation(s)
- Axel Hutt
- MLMS, MIMESIS, Université de Strasbourg, CNRS, Inria, ICube, 67000 Strasbourg, France
| | - Daniel Trotter
- Department of Physics, University of Ottawa, Ottawa, Ontario K1N 6N5, Canada
- Krembil Brain Institute, University Health Network, Toronto, Ontario M5T 0S8, Canada
| | - Aref Pariz
- Krembil Brain Institute, University Health Network, Toronto, Ontario M5T 0S8, Canada
- Department of Biology, University of Ottawa, Ottawa, Ontario K1N 6N5, Canada
| | - Taufik A Valiante
- Krembil Brain Institute, University Health Network, Toronto, Ontario M5T 0S8, Canada
- Department of Electrical and Computer Engineering, Institute of Medical Science, Institute of Biomedical Engineering, Division of Neurosurgery, Department of Surgery, CRANIA (Center for Advancing Neurotechnological Innovation to Application), Max Planck-University of Toronto Center for Neural Science and Technology, University of Toronto, Toronto, Ontario M5S 3G8, Canada
| | - Jérémie Lefebvre
- Department of Physics, University of Ottawa, Ottawa, Ontario K1N 6N5, Canada
- Krembil Brain Institute, University Health Network, Toronto, Ontario M5T 0S8, Canada
- Department of Biology, University of Ottawa, Ottawa, Ontario K1N 6N5, Canada
- Department of Mathematics, University of Toronto, Toronto, Ontario M5S 2E4, Canada
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5
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Lefebvre J, Hutt A. Induced synchronization by endogenous noise modulation in finite-size random neural networks: A stochastic mean-field study. CHAOS (WOODBURY, N.Y.) 2023; 33:123110. [PMID: 38055720 DOI: 10.1063/5.0167771] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 11/09/2023] [Indexed: 12/08/2023]
Abstract
Event-related synchronization and desynchronization (ERS/ERD) are well-known features found experimentally in brain signals during cognitive tasks. Their understanding promises to have much better insights into neural information processes in cognition. Under the hypothesis that neural information affects the endogenous neural noise level in populations, we propose to employ a stochastic mean-field model to explain ERS/ERD in the γ-frequency range. The work extends previous mean-field studies by deriving novel effects from finite network size. Moreover, numerical simulations of ERS/ERD and their analytical explanation by the mean-field model suggest several endogenous noise modulation schemes, which may modulate the system's synchronization.
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Affiliation(s)
- J Lefebvre
- Krembil Brain Institute, University Health Network, Toronto, Ontario M5T 0S8, Canada
- Department of Biology, University of Ottawa, Ottawa, Ontario K1N 6N5, Canada
- Department of Mathematics, University of Toronto, Toronto, Ontario M5S 2E4, Canada
| | - A Hutt
- ICube, MLMS, University of Strasbourg, MIMESIS Team, Inria Nancy-Grand Est, 67000 Strasbourg, France
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6
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Arnaudon A, Reva M, Zbili M, Markram H, Van Geit W, Kanari L. Controlling morpho-electrophysiological variability of neurons with detailed biophysical models. iScience 2023; 26:108222. [PMID: 37953946 PMCID: PMC10638024 DOI: 10.1016/j.isci.2023.108222] [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: 05/08/2023] [Revised: 07/21/2023] [Accepted: 10/12/2023] [Indexed: 11/14/2023] Open
Abstract
Variability, which is known to be a universal feature among biological units such as neuronal cells, holds significant importance, as, for example, it enables a robust encoding of a high volume of information in neuronal circuits and prevents hypersynchronizations. While most computational studies on electrophysiological variability in neuronal circuits were done with single-compartment neuron models, we instead focus on the variability of detailed biophysical models of neuron multi-compartmental morphologies. We leverage a Markov chain Monte Carlo method to generate populations of electrical models reproducing the variability of experimental recordings while being compatible with a set of morphologies to faithfully represent specifi morpho-electrical type. We demonstrate our approach on layer 5 pyramidal cells and study the morpho-electrical variability and in particular, find that morphological variability alone is insufficient to reproduce electrical variability. Overall, this approach provides a strong statistical basis to create detailed models of neurons with controlled variability.
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Affiliation(s)
- Alexis Arnaudon
- Blue Brain Project, École Polytechnique Fédérale de Lausanne (EPFL), Campus Biotech, Geneva, Switzerland
| | - Maria Reva
- Blue Brain Project, École Polytechnique Fédérale de Lausanne (EPFL), Campus Biotech, Geneva, Switzerland
| | - Mickael Zbili
- Blue Brain Project, École Polytechnique Fédérale de Lausanne (EPFL), Campus Biotech, Geneva, Switzerland
| | - Henry Markram
- Blue Brain Project, École Polytechnique Fédérale de Lausanne (EPFL), Campus Biotech, Geneva, Switzerland
| | - Werner Van Geit
- Blue Brain Project, École Polytechnique Fédérale de Lausanne (EPFL), Campus Biotech, Geneva, Switzerland
| | - Lida Kanari
- Blue Brain Project, École Polytechnique Fédérale de Lausanne (EPFL), Campus Biotech, Geneva, Switzerland
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7
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Liu C, Wu ZX, Guan JY. Nonmonotonic enhancement of diversity-induced resonance in systems of mobile oscillators. Phys Rev E 2023; 108:054209. [PMID: 38115517 DOI: 10.1103/physreve.108.054209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Accepted: 10/15/2023] [Indexed: 12/21/2023]
Abstract
Diversity is omnipresent in natural and synthetic extended systems, the phenomenon of diversity-induced resonance (DIR), wherein a moderate degree of the diversity can provoke an optimal collective response, provides researchers a brand-new strategy to amplify and utilize the weak signal. As yet the relevant advances focus mostly on the ideal situations where the interactions among elements are uncorrelated with the physical proximity of agents. Such a consideration overlooks interactions mediated by the motion of agents in space. Here, we investigate the signal response of an ensemble of spatial mobile heterogeneous bistable oscillators with two canonical interacting modes: dynamic and preset. The oscillators are considered as mass points and perform random walks in a two-dimensional square plane. Under the dynamic scheme, the oscillators can only interact with other oscillators within a fixed vision radius. For the preset circumstance, the interaction among oscillators occurs only when all of them are in a predefined region at the same moment. We find that the DIR can be obtained in both situations. Additionally, the strength of resonance nonmonotonically rises with respect to the increase of moving speed, and the optimal resonance is acquired by an intermediate magnitude of speed. Finally, we propose reduced equations to guarantee the occurrence of such mobility-optimized DIR on the basis of the fast switching approximation theory and also examine the robustness of such phenomenon through the excitable FitzHugh-Nagumo model and a different spatial motion mechanism. Our results reveal for the first time that the DIR can be optimized by the spatial mobility and thus has promising potential application in the communication of mobile agents.
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Affiliation(s)
- Cong Liu
- Lanzhou Center for Theoretical Physics, Key Laboratory of Theoretical Physics of Gansu Province, and Key Laboratory of Quantum Theory and Applications of MoE, Lanzhou University, Lanzhou, Gansu 730000, China and Institute of Computational Physics and Complex Systems, Lanzhou University, Lanzhou, Gansu 730000, China
| | - Zhi-Xi Wu
- Lanzhou Center for Theoretical Physics, Key Laboratory of Theoretical Physics of Gansu Province, and Key Laboratory of Quantum Theory and Applications of MoE, Lanzhou University, Lanzhou, Gansu 730000, China and Institute of Computational Physics and Complex Systems, Lanzhou University, Lanzhou, Gansu 730000, China
| | - Jian-Yue Guan
- Lanzhou Center for Theoretical Physics, Key Laboratory of Theoretical Physics of Gansu Province, and Key Laboratory of Quantum Theory and Applications of MoE, Lanzhou University, Lanzhou, Gansu 730000, China and Institute of Computational Physics and Complex Systems, Lanzhou University, Lanzhou, Gansu 730000, China
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8
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Chameh HM, Falby M, Movahed M, Arbabi K, Rich S, Zhang L, Lefebvre J, Tripathy SJ, De Pittà M, Valiante TA. Distinctive biophysical features of human cell-types: insights from studies of neurosurgically resected brain tissue. Front Synaptic Neurosci 2023; 15:1250834. [PMID: 37860223 PMCID: PMC10584155 DOI: 10.3389/fnsyn.2023.1250834] [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: 06/30/2023] [Accepted: 08/21/2023] [Indexed: 10/21/2023] Open
Abstract
Electrophysiological characterization of live human tissue from epilepsy patients has been performed for many decades. Although initially these studies sought to understand the biophysical and synaptic changes associated with human epilepsy, recently, it has become the mainstay for exploring the distinctive biophysical and synaptic features of human cell-types. Both epochs of these human cellular electrophysiological explorations have faced criticism. Early studies revealed that cortical pyramidal neurons obtained from individuals with epilepsy appeared to function "normally" in comparison to neurons from non-epilepsy controls or neurons from other species and thus there was little to gain from the study of human neurons from epilepsy patients. On the other hand, contemporary studies are often questioned for the "normalcy" of the recorded neurons since they are derived from epilepsy patients. In this review, we discuss our current understanding of the distinct biophysical features of human cortical neurons and glia obtained from tissue removed from patients with epilepsy and tumors. We then explore the concept of within cell-type diversity and its loss (i.e., "neural homogenization"). We introduce neural homogenization to help reconcile the epileptogenicity of seemingly "normal" human cortical cells and circuits. We propose that there should be continued efforts to study cortical tissue from epilepsy patients in the quest to understand what makes human cell-types "human".
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Affiliation(s)
- Homeira Moradi Chameh
- Division of Clinical and Computational Neuroscience, Krembil Brain Institute, University Health Network (UHN), Toronto, ON, Canada
| | - Madeleine Falby
- Division of Clinical and Computational Neuroscience, Krembil Brain Institute, University Health Network (UHN), Toronto, ON, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Mandana Movahed
- Division of Clinical and Computational Neuroscience, Krembil Brain Institute, University Health Network (UHN), Toronto, ON, Canada
| | - Keon Arbabi
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Scott Rich
- Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, ON, Canada
| | - Liang Zhang
- Division of Clinical and Computational Neuroscience, Krembil Brain Institute, University Health Network (UHN), Toronto, ON, Canada
| | - Jérémie Lefebvre
- Division of Clinical and Computational Neuroscience, Krembil Brain Institute, University Health Network (UHN), Toronto, ON, Canada
- Department of Biology, University of Ottawa, Ottawa, ON, Canada
- Department of Mathematics, University of Toronto, Toronto, ON, Canada
| | - Shreejoy J. Tripathy
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Maurizio De Pittà
- Division of Clinical and Computational Neuroscience, Krembil Brain Institute, University Health Network (UHN), Toronto, ON, Canada
- Department of Physiology, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
- Basque Center for Applied Mathematics, Bilbao, Spain
- Faculty of Medicine, University of the Basque Country, Leioa, Spain
| | - Taufik A. Valiante
- Division of Clinical and Computational Neuroscience, Krembil Brain Institute, University Health Network (UHN), Toronto, ON, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
- Institute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada
- Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON, Canada
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada
- Center for Advancing Neurotechnological Innovation to Application (CRANIA), Toronto, ON, Canada
- Max Planck-University of Toronto Center for Neural Science and Technology, University of Toronto, Toronto, ON, Canada
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9
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Varghese N, Moscoso B, Chavez A, Springer K, Ortiz E, Soh H, Santaniello S, Maheshwari A, Tzingounis AV. KCNQ2/3 Gain-of-Function Variants and Cell Excitability: Differential Effects in CA1 versus L2/3 Pyramidal Neurons. J Neurosci 2023; 43:6479-6494. [PMID: 37607817 PMCID: PMC10513074 DOI: 10.1523/jneurosci.0980-23.2023] [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: 05/26/2023] [Revised: 08/09/2023] [Accepted: 08/15/2023] [Indexed: 08/24/2023] Open
Abstract
Gain-of-function (GOF) pathogenic variants in the potassium channels KCNQ2 and KCNQ3 lead to hyperexcitability disorders such as epilepsy and autism spectrum disorders. However, the underlying cellular mechanisms of how these variants impair forebrain function are unclear. Here, we show that the R201C variant in KCNQ2 has opposite effects on the excitability of two types of mouse pyramidal neurons of either sex, causing hyperexcitability in layer 2/3 (L2/3) pyramidal neurons and hypoexcitability in CA1 pyramidal neurons. Similarly, the homologous R231C variant in KCNQ3 leads to hyperexcitability in L2/3 pyramidal neurons and hypoexcitability in CA1 pyramidal neurons. However, the effects of KCNQ3 gain-of-function on excitability are specific to superficial CA1 pyramidal neurons. These findings reveal a new level of complexity in the function of KCNQ2 and KCNQ3 channels in the forebrain and provide a framework for understanding the effects of gain-of-function variants and potassium channels in the brain.SIGNIFICANCE STATEMENT KCNQ2/3 gain-of-function (GOF) variants lead to severe forms of neurodevelopmental disorders, but the mechanisms by which these channels affect neuronal activity are poorly understood. In this study, using a series of transgenic mice we demonstrate that the same KCNQ2/3 GOF variants can lead to either hyperexcitability or hypoexcitability in different types of pyramidal neurons [CA1 vs layer (L)2/3]. Additionally, we show that expression of the recurrent KCNQ2 GOF variant R201C in forebrain pyramidal neurons could lead to seizures and SUDEP. Our data suggest that the effects of KCNQ2/3 GOF variants depend on specific cell types and brain regions, possibly accounting for the diverse range of phenotypes observed in individuals with KCNQ2/3 GOF variants.
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Affiliation(s)
- Nissi Varghese
- Department of Physiology and Neurobiology, University of Connecticut, Storrs, Connecticut 06269
| | - Bruno Moscoso
- Department of Neurology, Baylor College of Medicine, Houston, Texas 77030
| | - Ana Chavez
- Department of Neurology, Baylor College of Medicine, Houston, Texas 77030
| | - Kristen Springer
- Department of Physiology and Neurobiology, University of Connecticut, Storrs, Connecticut 06269
| | - Erika Ortiz
- Department of Neurology, Baylor College of Medicine, Houston, Texas 77030
| | - Heun Soh
- Department of Physiology and Neurobiology, University of Connecticut, Storrs, Connecticut 06269
| | - Sabato Santaniello
- Department of Biomedical Engineering and Connecticut Institute for the Brain and Cognitive Sciences, University of Connecticut, Storrs, Connecticut 06269
| | - Atul Maheshwari
- Department of Neurology, Baylor College of Medicine, Houston, Texas 77030
| | - Anastasios V Tzingounis
- Department of Physiology and Neurobiology, University of Connecticut, Storrs, Connecticut 06269
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10
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Inibhunu H, Moradi Chameh H, Skinner F, Rich S, Valiante TA. Hyperpolarization-Activated Cation Channels Shape the Spiking Frequency Preference of Human Cortical Layer 5 Pyramidal Neurons. eNeuro 2023; 10:ENEURO.0215-23.2023. [PMID: 37567768 PMCID: PMC10467019 DOI: 10.1523/eneuro.0215-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 07/19/2023] [Accepted: 07/20/2023] [Indexed: 08/13/2023] Open
Abstract
Discerning the contribution of specific ionic currents to complex neuronal dynamics is a difficult, but important, task. This challenge is exacerbated in the human setting, although the widely characterized uniqueness of the human brain compared with preclinical models necessitates the direct study of human neurons. Neuronal spiking frequency preference is of particular interest given its role in rhythm generation and signal transmission in cortical circuits. Here, we combine the frequency-dependent gain (FDG), a measure of spiking frequency preference, and novel in silico analyses to dissect the contributions of individual ionic currents to the suprathreshold features of human layer 5 (L5) neurons captured by the FDG. We confirm that a contemporary model of such a neuron, primarily constrained to capture subthreshold activity driven by the hyperpolarization-activated cyclic nucleotide gated (h-) current, replicates key features of the in vitro FDG both with and without h-current activity. With the model confirmed as a viable approximation of the biophysical features of interest, we applied new analysis techniques to quantify the activity of each modeled ionic current in the moments before spiking, revealing unique dynamics of the h-current. These findings motivated patch-clamp recordings in analogous rodent neurons to characterize their FDG, which confirmed that a biophysically detailed model of these neurons captures key interspecies differences in the FDG. These differences are correlated with distinct contributions of the h-current to neuronal activity. Together, this interdisciplinary and multispecies study provides new insights directly relating the dynamics of the h-current to suprathreshold spiking frequency preference in human L5 neurons.
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Affiliation(s)
- Happy Inibhunu
- Division of Clinical and Computational Neuroscience, Krembil Brain Institute, University Health Network, Toronto, Ontario M5T 1M8, Canada
| | - Homeira Moradi Chameh
- Division of Clinical and Computational Neuroscience, Krembil Brain Institute, University Health Network, Toronto, Ontario M5T 1M8, Canada
| | - Frances Skinner
- Division of Clinical and Computational Neuroscience, Krembil Brain Institute, University Health Network, Toronto, Ontario M5T 1M8, Canada
- Departments of Medicine, Neurology and Physiology, University of Toronto, Toronto, Ontario M5S 3H2, Canada
| | - Scott Rich
- Division of Clinical and Computational Neuroscience, Krembil Brain Institute, University Health Network, Toronto, Ontario M5T 1M8, Canada
| | - Taufik A Valiante
- Division of Clinical and Computational Neuroscience, Krembil Brain Institute, University Health Network, Toronto, Ontario M5T 1M8, Canada
- Institute of Biomedical Engineering, University of Toronto, Toronto, Ontario M5S 3E2, Canada
- Electrical and Computer Engineering, University of Toronto, Toronto, Ontario M5S 3G4, Canada
- Institute of Medical Science, University of Toronto, Toronto, Ontario M5S 1A8, Canada
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, Ontario M5T 1P5, Canada
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11
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Marinho LSR, Chiarantin GMD, Ikebara JM, Cardoso DS, de Lima-Vasconcellos TH, Higa GSV, Ferraz MSA, De Pasquale R, Takada SH, Papes F, Muotri AR, Kihara AH. The impact of antidepressants on human neurodevelopment: Brain organoids as experimental tools. Semin Cell Dev Biol 2023; 144:67-76. [PMID: 36115764 DOI: 10.1016/j.semcdb.2022.09.007] [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: 07/06/2022] [Revised: 09/10/2022] [Accepted: 09/10/2022] [Indexed: 11/23/2022]
Abstract
The use of antidepressants during pregnancy benefits the mother's well-being, but the effects of such substances on neurodevelopment remain poorly understood. Moreover, the consequences of early exposure to antidepressants may not be immediately apparent at birth. In utero exposure to selective serotonin reuptake inhibitors (SSRIs) has been related to developmental abnormalities, including a reduced white matter volume. Several reports have observed an increased incidence of autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) after prenatal exposure to SSRIs such as sertraline, the most widely prescribed SSRI. The advent of human-induced pluripotent stem cell (hiPSC) methods and assays now offers appropriate tools to test the consequences of such compounds for neurodevelopment in vitro. In particular, hiPSCs can be used to generate cerebral organoids - self-organized structures that recapitulate the morphology and complex physiology of the developing human brain, overcoming the limitations found in 2D cell culture and experimental animal models for testing drug efficacy and side effects. For example, single-cell RNA sequencing (scRNA-seq) and electrophysiological measurements on organoids can be used to evaluate the impact of antidepressants on the transcriptome and neuronal activity signatures in developing neurons. While the analysis of large-scale transcriptomic data depends on dimensionality reduction methods, electrophysiological recordings rely on temporal data series to discriminate statistical characteristics of neuronal activity, allowing for the rigorous analysis of the effects of antidepressants and other molecules that affect the developing nervous system, especially when applied in combination with relevant human cellular models such as brain organoids.
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Affiliation(s)
| | | | - Juliane Midori Ikebara
- Neurogenetics Laboratory, Universidade Federal do ABC, São Bernardo do Campo, SP 09606-045, Brazil
| | - Débora Sterzeck Cardoso
- Neurogenetics Laboratory, Universidade Federal do ABC, São Bernardo do Campo, SP 09606-045, Brazil
| | | | - Guilherme Shigueto Vilar Higa
- Neurogenetics Laboratory, Universidade Federal do ABC, São Bernardo do Campo, SP 09606-045, Brazil; Department of Physiology and Biophysics, Biomedical Sciences Institute I, São Paulo University, São Paulo, SP 05508-000, Brazil
| | | | - Roberto De Pasquale
- Department of Physiology and Biophysics, Biomedical Sciences Institute I, São Paulo University, São Paulo, SP 05508-000, Brazil
| | - Silvia Honda Takada
- Neurogenetics Laboratory, Universidade Federal do ABC, São Bernardo do Campo, SP 09606-045, Brazil
| | - Fabio Papes
- Department of Genetics, Evolution, Microbiology and Immunology, Institute of Biology, University of Campinas, Campinas, SP 13083-862, Brazil; Center for Medicinal Chemistry, University of Campinas, Campinas, SP 13083-875, Brazil; Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, CA 92093, USA
| | - Alysson R Muotri
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, CA 92093, USA; Department of Cellular & Molecular Medicine, University of California San Diego, School of Medicine, Center for Academic Research and Training in Anthropogeny, Kavli Institute for Brain and Mind, Archealization Center (ArchC), La Jolla, CA 92037, USA.
| | - Alexandre Hiroaki Kihara
- Neurogenetics Laboratory, Universidade Federal do ABC, São Bernardo do Campo, SP 09606-045, Brazil.
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12
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Hutt A, Rich S, Valiante TA, Lefebvre J. Intrinsic neural diversity quenches the dynamic volatility of neural networks. Proc Natl Acad Sci U S A 2023; 120:e2218841120. [PMID: 37399421 PMCID: PMC10334753 DOI: 10.1073/pnas.2218841120] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Accepted: 05/19/2023] [Indexed: 07/05/2023] Open
Abstract
Heterogeneity is the norm in biology. The brain is no different: Neuronal cell types are myriad, reflected through their cellular morphology, type, excitability, connectivity motifs, and ion channel distributions. While this biophysical diversity enriches neural systems' dynamical repertoire, it remains challenging to reconcile with the robustness and persistence of brain function over time (resilience). To better understand the relationship between excitability heterogeneity (variability in excitability within a population of neurons) and resilience, we analyzed both analytically and numerically a nonlinear sparse neural network with balanced excitatory and inhibitory connections evolving over long time scales. Homogeneous networks demonstrated increases in excitability, and strong firing rate correlations-signs of instability-in response to a slowly varying modulatory fluctuation. Excitability heterogeneity tuned network stability in a context-dependent way by restraining responses to modulatory challenges and limiting firing rate correlations, while enriching dynamics during states of low modulatory drive. Excitability heterogeneity was found to implement a homeostatic control mechanism enhancing network resilience to changes in population size, connection probability, strength and variability of synaptic weights, by quenching the volatility (i.e., its susceptibility to critical transitions) of its dynamics. Together, these results highlight the fundamental role played by cell-to-cell heterogeneity in the robustness of brain function in the face of change.
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Affiliation(s)
- Axel Hutt
- Université de Strasbourg, CNRS, Inria, ICube, MLMS, MIMESIS, StrasbourgF-67000, France
| | - Scott Rich
- Krembil Brain Institute, Division of Clinical and Computational Neuroscience, University Health Network, Toronto, ONM5T 0S8, Canada
| | - Taufik A. Valiante
- Krembil Brain Institute, Division of Clinical and Computational Neuroscience, University Health Network, Toronto, ONM5T 0S8, Canada
- Department of Electrical and Computer Engineering, University of Toronto, Toronto, ONM5S 3G8, Canada
- Institute of Biomedical Engineering, University of Toronto, Toronto, ONM5S 3G9, Canada
- Institute of Medical Sciences, University of Toronto, Toronto, ONM5S 1A8, Canada
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ONM5G 2C4, Canada
- Center for Advancing Neurotechnological Innovation to Application, University of Toronto, Toronto, ONM5G 2A2, Canada
- Max Planck-University of Toronto Center for Neural Science and Technology, University of Toronto, Toronto, ONM5S 3G8, Canada
| | - Jérémie Lefebvre
- Krembil Brain Institute, Division of Clinical and Computational Neuroscience, University Health Network, Toronto, ONM5T 0S8, Canada
- Department of Biology, University of Ottawa, Ottawa, ONK1N 6N5, Canada
- Department of Mathematics, University of Toronto, Toronto, ONM5S 2E4, Canada
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13
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Hull JM, Denomme N, Yuan Y, Booth V, Isom LL. Heterogeneity of voltage gated sodium current density between neurons decorrelates spiking and suppresses network synchronization in Scn1b null mouse models. Sci Rep 2023; 13:8887. [PMID: 37264112 PMCID: PMC10235421 DOI: 10.1038/s41598-023-36036-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Accepted: 05/28/2023] [Indexed: 06/03/2023] Open
Abstract
Voltage gated sodium channels (VGSCs) are required for action potential initiation and propagation in mammalian neurons. As with other ion channel families, VGSC density varies between neurons. Importantly, sodium current (INa) density variability is reduced in pyramidal neurons of Scn1b null mice. Scn1b encodes the VGSC β1/ β1B subunits, which regulate channel expression, trafficking, and voltage dependent properties. Here, we investigate how variable INa density in cortical layer 6 and subicular pyramidal neurons affects spike patterning and network synchronization. Constitutive or inducible Scn1b deletion enhances spike timing correlations between pyramidal neurons in response to fluctuating stimuli and impairs spike-triggered average current pattern diversity while preserving spike reliability. Inhibiting INa with a low concentration of tetrodotoxin similarly alters patterning without impairing reliability, with modest effects on firing rate. Computational modeling shows that broad INa density ranges confer a similarly broad spectrum of spike patterning in response to fluctuating synaptic conductances. Network coupling of neurons with high INa density variability displaces the coupling requirements for synchronization and broadens the dynamic range of activity when varying synaptic strength and network topology. Our results show that INa heterogeneity between neurons potently regulates spike pattern diversity and network synchronization, expanding VGSC roles in the nervous system.
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Affiliation(s)
- Jacob M Hull
- Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI, 48109, USA
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, 94305, USA
| | - Nicholas Denomme
- Department of Pharmacology, University of Michigan, Ann Arbor, MI, 48109, USA
- Department of Anesthesiology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Yukun Yuan
- Department of Pharmacology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Victoria Booth
- Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI, 48109, USA
- Department of Mathematics, University of Michigan, Ann Arbor, MI, 48109, USA
- Department of Anesthesiology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Lori L Isom
- Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI, 48109, USA.
- Department of Pharmacology, University of Michigan, Ann Arbor, MI, 48109, USA.
- Department of Molecular & Integrative Physiology, University of Michigan, Ann Arbor, MI, 48109, USA.
- Department of Neurology, University of Michigan, Ann Arbor, MI, 48109, USA.
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14
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Stöber TM, Batulin D, Triesch J, Narayanan R, Jedlicka P. Degeneracy in epilepsy: multiple routes to hyperexcitable brain circuits and their repair. Commun Biol 2023; 6:479. [PMID: 37137938 PMCID: PMC10156698 DOI: 10.1038/s42003-023-04823-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 04/06/2023] [Indexed: 05/05/2023] Open
Abstract
Due to its complex and multifaceted nature, developing effective treatments for epilepsy is still a major challenge. To deal with this complexity we introduce the concept of degeneracy to the field of epilepsy research: the ability of disparate elements to cause an analogous function or malfunction. Here, we review examples of epilepsy-related degeneracy at multiple levels of brain organisation, ranging from the cellular to the network and systems level. Based on these insights, we outline new multiscale and population modelling approaches to disentangle the complex web of interactions underlying epilepsy and to design personalised multitarget therapies.
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Affiliation(s)
- Tristan Manfred Stöber
- Frankfurt Institute for Advanced Studies, 60438, Frankfurt am Main, Germany
- Institute for Neural Computation, Faculty of Computer Science, Ruhr University Bochum, 44801, Bochum, Germany
- Epilepsy Center Frankfurt Rhine-Main, Department of Neurology, Goethe University, 60590, Frankfurt, Germany
| | - Danylo Batulin
- Frankfurt Institute for Advanced Studies, 60438, Frankfurt am Main, Germany
- CePTER - Center for Personalized Translational Epilepsy Research, Goethe University, 60590, Frankfurt, Germany
- Faculty of Computer Science and Mathematics, Goethe University, 60486, Frankfurt, Germany
| | - Jochen Triesch
- Frankfurt Institute for Advanced Studies, 60438, Frankfurt am Main, Germany
| | - Rishikesh Narayanan
- Cellular Neurophysiology Laboratory, Molecular Biophysics Unit, Indian Institute of Science, Bangalore, 560012, India
| | - Peter Jedlicka
- ICAR3R - Interdisciplinary Centre for 3Rs in Animal Research, Faculty of Medicine, Justus Liebig University Giessen, 35390, Giessen, Germany.
- Institute of Clinical Neuroanatomy, Neuroscience Center, Goethe University, 60590, Frankfurt am Main, Germany.
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15
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Depannemaecker D, Ezzati A, Wang H, Jirsa V, Bernard C. From phenomenological to biophysical models of seizures. Neurobiol Dis 2023; 182:106131. [PMID: 37086755 DOI: 10.1016/j.nbd.2023.106131] [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: 02/17/2023] [Revised: 04/12/2023] [Accepted: 04/14/2023] [Indexed: 04/24/2023] Open
Abstract
Epilepsy is a complex disease that requires various approaches for its study. In this short review, we discuss the contribution of theoretical and computational models. The review presents theoretical frameworks that underlie the understanding of certain seizure properties and their classification based on their dynamical properties at the onset and offset of seizures. Dynamical system tools are valuable resources in the study of seizures. By analyzing the complex, dynamic behavior of seizures, these tools can provide insights into seizure mechanisms and offer a framework for their classification. Additionally, computational models have high potential for clinical applications, as they can be used to develop more accurate diagnostic and personalized medicine tools. We discuss various modeling approaches that span different scales and levels, while also questioning the neurocentric view, and emphasize the importance of considering glial cells. Finally, we explore the epistemic value provided by this type of approach.
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Affiliation(s)
- Damien Depannemaecker
- Institut de Neurosciences des Syst' emes, Aix-Marseille University, INSERM, Marseille, France.
| | - Aitakin Ezzati
- Institut de Neurosciences des Syst' emes, Aix-Marseille University, INSERM, Marseille, France
| | - Huifang Wang
- Institut de Neurosciences des Syst' emes, Aix-Marseille University, INSERM, Marseille, France
| | - Viktor Jirsa
- Institut de Neurosciences des Syst' emes, Aix-Marseille University, INSERM, Marseille, France
| | - Christophe Bernard
- Institut de Neurosciences des Syst' emes, Aix-Marseille University, INSERM, Marseille, France.
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16
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Balcioglu A, Gillani R, Doron M, Burnell K, Ku T, Erisir A, Chung K, Segev I, Nedivi E. Mapping thalamic innervation to individual L2/3 pyramidal neurons and modeling their 'readout' of visual input. Nat Neurosci 2023; 26:470-480. [PMID: 36732641 DOI: 10.1038/s41593-022-01253-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Accepted: 12/21/2022] [Indexed: 02/04/2023]
Abstract
The thalamus is the main gateway for sensory information from the periphery to the mammalian cerebral cortex. A major conundrum has been the discrepancy between the thalamus's central role as the primary feedforward projection system into the neocortex and the sparseness of thalamocortical synapses. Here we use new methods, combining genetic tools and scalable tissue expansion microscopy for whole-cell synaptic mapping, revealing the number, density and size of thalamic versus cortical excitatory synapses onto individual layer 2/3 (L2/3) pyramidal cells (PCs) of the mouse primary visual cortex. We find that thalamic inputs are not only sparse, but remarkably heterogeneous in number and density across individual dendrites and neurons. Most surprising, despite their sparseness, thalamic synapses onto L2/3 PCs are smaller than their cortical counterparts. Incorporating these findings into fine-scale, anatomically faithful biophysical models of L2/3 PCs reveals how individual neurons with sparse and weak thalamocortical synapses, embedded in small heterogeneous neuronal ensembles, may reliably 'read out' visually driven thalamic input.
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Affiliation(s)
- Aygul Balcioglu
- Picower Institute for Learning and Memory, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Rebecca Gillani
- Picower Institute for Learning and Memory, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Michael Doron
- The Edmond and Lily Safra Center for Brain Sciences, Jerusalem, Israel
- Department of Neurobiology, The Hebrew University of Jerusalem, Jerusalem, Israel
- Broad Institute of Harvard University and MIT, Cambridge, MA, USA
| | - Kendyll Burnell
- Picower Institute for Learning and Memory, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Taeyun Ku
- Picower Institute for Learning and Memory, Cambridge, MA, USA
- Institute for Medical Engineering and Science, Cambridge, MA, USA
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea
| | - Alev Erisir
- Department of Psychology, University of Virginia, Charlottesville, VA, USA
| | - Kwanghun Chung
- Picower Institute for Learning and Memory, Cambridge, MA, USA
- Department of Neurobiology, The Hebrew University of Jerusalem, Jerusalem, Israel
- Institute for Medical Engineering and Science, Cambridge, MA, USA
- Broad Institute of Harvard University and MIT, Cambridge, MA, USA
| | - Idan Segev
- The Edmond and Lily Safra Center for Brain Sciences, Jerusalem, Israel
- Department of Neurobiology, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Elly Nedivi
- Picower Institute for Learning and Memory, Cambridge, MA, USA.
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA.
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17
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Gast R, Solla SA, Kennedy A. Macroscopic dynamics of neural networks with heterogeneous spiking thresholds. Phys Rev E 2023; 107:024306. [PMID: 36932598 DOI: 10.1103/physreve.107.024306] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Accepted: 02/02/2023] [Indexed: 06/18/2023]
Abstract
Mean-field theory links the physiological properties of individual neurons to the emergent dynamics of neural population activity. These models provide an essential tool for studying brain function at different scales; however, for their application to neural populations on large scale, they need to account for differences between distinct neuron types. The Izhikevich single neuron model can account for a broad range of different neuron types and spiking patterns, thus rendering it an optimal candidate for a mean-field theoretic treatment of brain dynamics in heterogeneous networks. Here we derive the mean-field equations for networks of all-to-all coupled Izhikevich neurons with heterogeneous spiking thresholds. Using methods from bifurcation theory, we examine the conditions under which the mean-field theory accurately predicts the dynamics of the Izhikevich neuron network. To this end, we focus on three important features of the Izhikevich model that are subject here to simplifying assumptions: (i) spike-frequency adaptation, (ii) the spike reset conditions, and (iii) the distribution of single-cell spike thresholds across neurons. Our results indicate that, while the mean-field model is not an exact model of the Izhikevich network dynamics, it faithfully captures its different dynamic regimes and phase transitions. We thus present a mean-field model that can represent different neuron types and spiking dynamics. The model comprises biophysical state variables and parameters, incorporates realistic spike resetting conditions, and accounts for heterogeneity in neural spiking thresholds. These features allow for a broad applicability of the model as well as for a direct comparison to experimental data.
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Affiliation(s)
- Richard Gast
- Department of Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago, Illinois 60611, USA
| | - Sara A Solla
- Department of Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago, Illinois 60611, USA
| | - Ann Kennedy
- Department of Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago, Illinois 60611, USA
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18
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Aussel A, Ranta R, Aron O, Colnat-Coulbois S, Maillard L, Buhry L. Cell to network computational model of the epileptic human hippocampus suggests specific roles of network and channel dysfunctions in the ictal and interictal oscillations. J Comput Neurosci 2022; 50:519-535. [PMID: 35971033 DOI: 10.1007/s10827-022-00829-5] [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: 12/16/2020] [Revised: 07/03/2022] [Accepted: 07/12/2022] [Indexed: 10/15/2022]
Abstract
The mechanisms underlying the generation of hippocampal epileptic seizures and interictal events and their interactions with the sleep-wake cycle are not yet fully understood. Indeed, medial temporal lobe epilepsy is associated with hippocampal abnormalities both at the neuronal (channelopathies, impaired potassium and chloride dynamics) and network level (neuronal and axonal loss, mossy fiber sprouting), with more frequent seizures during wakefulness compared with slow-wave sleep. In this article, starting from our previous computational modeling work of the hippocampal formation based on realistic topology and synaptic connectivity, we study the role of micro- and mesoscale pathological conditions of the epileptic hippocampus in the generation and maintenance of seizure-like theta and interictal oscillations. We show, through the simulations of hippocampal activity during slow-wave sleep and wakefulness that: (i) both mossy fiber sprouting and sclerosis account for seizure-like theta activity, (ii) but they have antagonist effects (seizure-like activity occurrence increases with sprouting but decreases with sclerosis), (iii) though impaired potassium and chloride dynamics have little influence on the generation of seizure-like activity, they do play a role on the generation of interictal patterns, and (iv) seizure-like activity and fast ripples are more likely to occur during wakefulness and interictal spikes during sleep.
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Affiliation(s)
- Amélie Aussel
- Laboratoire Lorrain de Recherche en Informatique et ses applications (LORIA UMR 7503), University of Lorraine, 54506, Nancy, France. .,Centre de Recherche en Automatique de Nancy, University of Lorraine, CRAN-CNRS UMR 7039, Nancy, France.
| | - Radu Ranta
- Centre de Recherche en Automatique de Nancy, University of Lorraine, CRAN-CNRS UMR 7039, Nancy, France
| | - Olivier Aron
- Centre de Recherche en Automatique de Nancy, University of Lorraine, CRAN-CNRS UMR 7039, Nancy, France.,Department of Neurology, CHU de Nancy, Nancy, France
| | - Sophie Colnat-Coulbois
- Centre de Recherche en Automatique de Nancy, University of Lorraine, CRAN-CNRS UMR 7039, Nancy, France.,Department of Neurology, CHU de Nancy, Nancy, France
| | - Louise Maillard
- Centre de Recherche en Automatique de Nancy, University of Lorraine, CRAN-CNRS UMR 7039, Nancy, France.,Department of Neurology, CHU de Nancy, Nancy, France
| | - Laure Buhry
- Laboratoire Lorrain de Recherche en Informatique et ses applications (LORIA UMR 7503), University of Lorraine, 54506, Nancy, France
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19
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Molecular Mechanisms of Epilepsy: The Role of the Chloride Transporter KCC2. J Mol Neurosci 2022; 72:1500-1515. [PMID: 35819636 DOI: 10.1007/s12031-022-02041-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2022] [Accepted: 06/07/2022] [Indexed: 10/17/2022]
Abstract
Epilepsy is a neurological disease characterized by abnormal or synchronous brain activity causing seizures, which may produce convulsions, minor physical signs, or a combination of symptoms. These disorders affect approximately 65 million people worldwide, from all ages and genders. Seizures apart, epileptic patients present a high risk to develop neuropsychological comorbidities such as cognitive deficits, emotional disturbance, and psychiatric disorders, which severely impair quality of life. Currently, the treatment for epilepsy includes the administration of drugs or surgery, but about 30% of the patients treated with antiepileptic drugs develop time-dependent pharmacoresistence. Therefore, further investigation about epilepsy and its causes is needed to find new pharmacological targets and innovative therapeutic strategies. Pharmacoresistance is associated to changes in neuronal plasticity and alterations of GABAA receptor-mediated neurotransmission. The downregulation of GABA inhibitory activity may arise from a positive shift in GABAA receptor reversal potential, due to an alteration in chloride homeostasis. In this paper, we review the contribution of K+-Cl--cotransporter (KCC2) to the alterations in the Cl- gradient observed in epileptic condition, and how these alterations are coupled to the increase in the excitability.
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