1
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Harris KM, Kuwajima M, Flores JC, Zito K. Synapse-specific structural plasticity that protects and refines local circuits during LTP and LTD. Philos Trans R Soc Lond B Biol Sci 2024; 379:20230224. [PMID: 38853547 DOI: 10.1098/rstb.2023.0224] [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: 10/17/2023] [Accepted: 01/05/2024] [Indexed: 06/11/2024] Open
Abstract
Synapses form trillions of connections in the brain. Long-term potentiation (LTP) and long-term depression (LTD) are cellular mechanisms vital for learning that modify the strength and structure of synapses. Three-dimensional reconstruction from serial section electron microscopy reveals three distinct pre- to post-synaptic arrangements: strong active zones (AZs) with tightly docked vesicles, weak AZs with loose or non-docked vesicles, and nascent zones (NZs) with a postsynaptic density but no presynaptic vesicles. Importantly, LTP can be temporarily saturated preventing further increases in synaptic strength. At the onset of LTP, vesicles are recruited to NZs, converting them to AZs. During recovery of LTP from saturation (1-4 h), new NZs form, especially on spines where AZs are most enlarged by LTP. Sentinel spines contain smooth endoplasmic reticulum (SER), have the largest synapses and form clusters with smaller spines lacking SER after LTP recovers. We propose a model whereby NZ plasticity provides synapse-specific AZ expansion during LTP and loss of weak AZs that drive synapse shrinkage during LTD. Spine clusters become functionally engaged during LTP or disassembled during LTD. Saturation of LTP or LTD probably acts to protect recently formed memories from ongoing plasticity and may account for the advantage of spaced over massed learning. This article is part of a discussion meeting issue 'Long-term potentiation: 50 years on'.
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Affiliation(s)
- Kristen M Harris
- Department of Neuroscience and Center for Learning and Memory, The University of Texas at Austin , Austin, TX 78712, USA
| | - Masaaki Kuwajima
- Department of Neuroscience and Center for Learning and Memory, The University of Texas at Austin , Austin, TX 78712, USA
| | - Juan C Flores
- Center for Neuroscience, University of California , Davis, CA 95618, USA
| | - Karen Zito
- Center for Neuroscience, University of California , Davis, CA 95618, USA
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2
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Xiao S, Yadav S, Jayant K. Probing multiplexed basal dendritic computations using two-photon 3D holographic uncaging. Cell Rep 2024; 43:114413. [PMID: 38943640 DOI: 10.1016/j.celrep.2024.114413] [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: 09/29/2022] [Revised: 05/06/2024] [Accepted: 06/12/2024] [Indexed: 07/01/2024] Open
Abstract
Basal dendrites of layer 5 cortical pyramidal neurons exhibit Na+ and N-methyl-D-aspartate receptor (NMDAR) regenerative spikes and are uniquely poised to influence somatic output. Nevertheless, due to technical limitations, how multibranch basal dendritic integration shapes and enables multiplexed barcoding of synaptic streams remains poorly mapped. Here, we combine 3D two-photon holographic transmitter uncaging, whole-cell dynamic clamp, and biophysical modeling to reveal how synchronously activated synapses (distributed and clustered) across multiple basal dendritic branches are multiplexed under quiescent and in vivo-like conditions. While dendritic regenerative Na+ spikes promote millisecond somatic spike precision, distributed synaptic inputs and NMDAR spikes regulate gain. These concomitantly occurring dendritic nonlinearities enable multiplexed information transfer amid an ongoing noisy background, including under back-propagating voltage resets, by barcoding the axo-somatic spike structure. Our results unveil a multibranch dendritic integration framework in which dendritic nonlinearities are critical for multiplexing different spatial-temporal synaptic input patterns, enabling optimal feature binding.
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Affiliation(s)
- Shulan Xiao
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, USA
| | - Saumitra Yadav
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, USA
| | - Krishna Jayant
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, USA; Purdue Institute for Integrative Neuroscience, Purdue University, West Lafayette, IN, USA.
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3
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Horton S, Mastrolia V, Jackson RE, Kemlo S, Pereira Machado PM, Carbajal MA, Hindges R, Fleck RA, Aguiar P, Neves G, Burrone J. Excitatory and inhibitory synapses show a tight subcellular correlation that weakens over development. Cell Rep 2024; 43:114361. [PMID: 38900634 DOI: 10.1016/j.celrep.2024.114361] [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: 02/09/2024] [Revised: 04/24/2024] [Accepted: 05/30/2024] [Indexed: 06/22/2024] Open
Abstract
Neurons receive correlated levels of excitation and inhibition, a feature that is important for proper brain function. However, how this relationship between excitatory and inhibitory inputs is established during the dynamic period of circuit wiring remains unexplored. Using multiple techniques, including in utero electroporation, electron microscopy, and electrophysiology, we reveal a tight correlation in the distribution of excitatory and inhibitory synapses along the dendrites of developing CA1 hippocampal neurons. This correlation was present within short dendritic stretches (<20 μm) and, surprisingly, was most pronounced during early development, sharply declining with maturity. The tight matching between excitation and inhibition was unexpected, as inhibitory synapses lacked an active zone when formed and exhibited compromised evoked release. We propose that inhibitory synapses form as a stabilizing scaffold to counterbalance growing excitation levels. This relationship diminishes over time, suggesting a critical role for a subcellular balance in early neuronal function and circuit formation.
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Affiliation(s)
- Sally Horton
- MRC Centre for Neurodevelopmental Disorders, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE1 1UL, UK; Centre for Developmental Neurobiology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE1 1UL, UK
| | - Vincenzo Mastrolia
- MRC Centre for Neurodevelopmental Disorders, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE1 1UL, UK; Centre for Developmental Neurobiology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE1 1UL, UK
| | - Rachel E Jackson
- MRC Centre for Neurodevelopmental Disorders, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE1 1UL, UK; Centre for Developmental Neurobiology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE1 1UL, UK
| | - Sarah Kemlo
- Centre for Developmental Neurobiology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE1 1UL, UK
| | - Pedro M Pereira Machado
- Centre for Ultrastructural Imaging (CUI), Kings College London, New Hunts House, Guys Hospital Campus, London SE1 1UL, UK
| | - Maria Alejandra Carbajal
- Centre for Ultrastructural Imaging (CUI), Kings College London, New Hunts House, Guys Hospital Campus, London SE1 1UL, UK
| | - Robert Hindges
- MRC Centre for Neurodevelopmental Disorders, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE1 1UL, UK; Centre for Developmental Neurobiology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE1 1UL, UK
| | - Roland A Fleck
- Centre for Ultrastructural Imaging (CUI), Kings College London, New Hunts House, Guys Hospital Campus, London SE1 1UL, UK
| | - Paulo Aguiar
- i3S-Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal
| | - Guilherme Neves
- MRC Centre for Neurodevelopmental Disorders, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE1 1UL, UK; Centre for Developmental Neurobiology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE1 1UL, UK.
| | - Juan Burrone
- MRC Centre for Neurodevelopmental Disorders, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE1 1UL, UK; Centre for Developmental Neurobiology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE1 1UL, UK.
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4
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Leighton AH, Cheyne JE, Lohmann C. Clustered synapses develop in distinct dendritic domains in visual cortex before eye opening. eLife 2024; 12:RP93498. [PMID: 38990761 PMCID: PMC11239177 DOI: 10.7554/elife.93498] [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] [Indexed: 07/13/2024] Open
Abstract
Synaptic inputs to cortical neurons are highly structured in adult sensory systems, such that neighboring synapses along dendrites are activated by similar stimuli. This organization of synaptic inputs, called synaptic clustering, is required for high-fidelity signal processing, and clustered synapses can already be observed before eye opening. However, how clustered inputs emerge during development is unknown. Here, we employed concurrent in vivo whole-cell patch-clamp and dendritic calcium imaging to map spontaneous synaptic inputs to dendrites of layer 2/3 neurons in the mouse primary visual cortex during the second postnatal week until eye opening. We found that the number of functional synapses and the frequency of transmission events increase several fold during this developmental period. At the beginning of the second postnatal week, synapses assemble specifically in confined dendritic segments, whereas other segments are devoid of synapses. By the end of the second postnatal week, just before eye opening, dendrites are almost entirely covered by domains of co-active synapses. Finally, co-activity with their neighbor synapses correlates with synaptic stabilization and potentiation. Thus, clustered synapses form in distinct functional domains presumably to equip dendrites with computational modules for high-capacity sensory processing when the eyes open.
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Affiliation(s)
- Alexandra H Leighton
- Department of Synapse and Network Development, Netherlands Institute for NeuroscienceAmsterdamNetherlands
| | - Juliette E Cheyne
- Department of Synapse and Network Development, Netherlands Institute for NeuroscienceAmsterdamNetherlands
| | - Christian Lohmann
- Department of Synapse and Network Development, Netherlands Institute for NeuroscienceAmsterdamNetherlands
- Department of Functional Genomics, Center for Neurogenomics and Cognitive Research, VU University AmsterdamAmsterdamNetherlands
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5
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Caya-Bissonnette L, Béïque JC. Half a century legacy of long-term potentiation. Curr Biol 2024; 34:R640-R662. [PMID: 38981433 DOI: 10.1016/j.cub.2024.05.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/11/2024]
Abstract
In 1973, two papers from Bliss and Lømo and from Bliss and Gardner-Medwin reported that high-frequency synaptic stimulation in the dentate gyrus of rabbits resulted in a long-lasting increase in synaptic strength. This form of synaptic plasticity, commonly referred to as long-term potentiation (LTP), was immediately considered as an attractive mechanism accounting for the ability of the brain to store information. In this historical piece looking back over the past 50 years, we discuss how these two landmark contributions directly motivated a colossal research effort and detail some of the resulting milestones that have shaped our evolving understanding of the molecular and cellular underpinnings of LTP. We highlight the main features of LTP, cover key experiments that defined its induction and expression mechanisms, and outline the evidence supporting a potential role of LTP in learning and memory. We also briefly explore some ramifications of LTP on network stability, consider current limitations of LTP as a model of associative memory, and entertain future research orientations.
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Affiliation(s)
- Léa Caya-Bissonnette
- Graduate Program in Neuroscience, University of Ottawa, 451 ch. Smyth Road (3501N), Ottawa, ON K1H 8M5, Canada; Brain and Mind Research Institute's Centre for Neural Dynamics and Artificial Intelligence, 451 ch. Smyth Road (3501N), Ottawa, ON K1H 8M5, Canada; Department of Cellular and Molecular Medicine, Faculty of Medicine, University of Ottawa, 451 ch. Smyth Road (3501N), Ottawa, ON K1H 8M5, Canada
| | - Jean-Claude Béïque
- Brain and Mind Research Institute's Centre for Neural Dynamics and Artificial Intelligence, 451 ch. Smyth Road (3501N), Ottawa, ON K1H 8M5, Canada; Department of Cellular and Molecular Medicine, Faculty of Medicine, University of Ottawa, 451 ch. Smyth Road (3501N), Ottawa, ON K1H 8M5, Canada.
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6
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Choucry A, Nomoto M, Inokuchi K. Engram mechanisms of memory linking and identity. Nat Rev Neurosci 2024; 25:375-392. [PMID: 38664582 DOI: 10.1038/s41583-024-00814-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/25/2024] [Indexed: 05/25/2024]
Abstract
Memories are thought to be stored in neuronal ensembles referred to as engrams. Studies have suggested that when two memories occur in quick succession, a proportion of their engrams overlap and the memories become linked (in a process known as prospective linking) while maintaining their individual identities. In this Review, we summarize the key principles of memory linking through engram overlap, as revealed by experimental and modelling studies. We describe evidence of the involvement of synaptic memory substrates, spine clustering and non-linear neuronal capacities in prospective linking, and suggest a dynamic somato-synaptic model, in which memories are shared between neurons yet remain separable through distinct dendritic and synaptic allocation patterns. We also bring into focus retrospective linking, in which memories become associated after encoding via offline reactivation, and discuss key temporal and mechanistic differences between prospective and retrospective linking, as well as the potential differences in their cognitive outcomes.
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Affiliation(s)
- Ali Choucry
- Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama, Japan
- Research Center for Idling Brain Science, University of Toyama, Toyama, Japan
- Department of Pharmacology and Toxicology, Faculty of Pharmacy, Cairo University, Cairo, Egypt
| | - Masanori Nomoto
- Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama, Japan
- Research Center for Idling Brain Science, University of Toyama, Toyama, Japan
- CREST, Japan Science and Technology Agency (JST), University of Toyama, Toyama, Japan
- Japan Agency for Medical Research and Development (AMED), Tokyo, Japan
| | - Kaoru Inokuchi
- Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama, Japan.
- Research Center for Idling Brain Science, University of Toyama, Toyama, Japan.
- CREST, Japan Science and Technology Agency (JST), University of Toyama, Toyama, Japan.
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7
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Moreno-Sanchez A, Vasserman AN, Jang H, Hina BW, von Reyn CR, Ausborn J. Morphology and synapse topography optimize linear encoding of synapse numbers in Drosophila looming responsive descending neurons. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.24.591016. [PMID: 38712267 PMCID: PMC11071487 DOI: 10.1101/2024.04.24.591016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Synapses are often precisely organized on dendritic arbors, yet the role of synaptic topography in dendritic integration remains poorly understood. Utilizing electron microscopy (EM) connectomics we investigate synaptic topography in Drosophila melanogaster looming circuits, focusing on retinotopically tuned visual projection neurons (VPNs) that synapse onto descending neurons (DNs). Synapses of a given VPN type project to non-overlapping regions on DN dendrites. Within these spatially constrained clusters, synapses are not retinotopically organized, but instead adopt near random distributions. To investigate how this organization strategy impacts DN integration, we developed multicompartment models of DNs fitted to experimental data and using precise EM morphologies and synapse locations. We find that DN dendrite morphologies normalize EPSP amplitudes of individual synaptic inputs and that near random distributions of synapses ensure linear encoding of synapse numbers from individual VPNs. These findings illuminate how synaptic topography influences dendritic integration and suggest that linear encoding of synapse numbers may be a default strategy established through connectivity and passive neuron properties, upon which active properties and plasticity can then tune as needed.
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Affiliation(s)
- Anthony Moreno-Sanchez
- Department of Neurobiology and Anatomy, Drexel University College of Medicine, Philadelphia, United States
| | - Alexander N. Vasserman
- Department of Neurobiology and Anatomy, Drexel University College of Medicine, Philadelphia, United States
| | - HyoJong Jang
- School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA, United States
| | - Bryce W. Hina
- School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA, United States
| | - Catherine R. von Reyn
- Department of Neurobiology and Anatomy, Drexel University College of Medicine, Philadelphia, United States
- School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA, United States
| | - Jessica Ausborn
- Department of Neurobiology and Anatomy, Drexel University College of Medicine, Philadelphia, United States
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8
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Lopez-Ortega E, Choi JY, Hong I, Roth RH, Cudmore RH, Huganir RL. Stimulus-dependent synaptic plasticity underlies neuronal circuitry refinement in the mouse primary visual cortex. Cell Rep 2024; 43:113966. [PMID: 38507408 PMCID: PMC11210464 DOI: 10.1016/j.celrep.2024.113966] [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: 05/05/2023] [Revised: 12/26/2023] [Accepted: 02/28/2024] [Indexed: 03/22/2024] Open
Abstract
Perceptual learning improves our ability to interpret sensory stimuli present in our environment through experience. Despite its importance, the underlying mechanisms that enable perceptual learning in our sensory cortices are still not fully understood. In this study, we used in vivo two-photon imaging to investigate the functional and structural changes induced by visual stimulation in the mouse primary visual cortex (V1). Our results demonstrate that repeated stimulation leads to a refinement of V1 circuitry by decreasing the number of responsive neurons while potentiating their response. At the synaptic level, we observe a reduction in the number of dendritic spines and an overall increase in spine AMPA receptor levels in the same subset of neurons. In addition, visual stimulation induces synaptic potentiation in neighboring spines within individual dendrites. These findings provide insights into the mechanisms of synaptic plasticity underlying information processing in the neocortex.
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Affiliation(s)
- Elena Lopez-Ortega
- Department of Neuroscience, Kavli Neuroscience Discovery Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Jung Yoon Choi
- Department of Neuroscience, Kavli Neuroscience Discovery Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Ingie Hong
- Department of Neuroscience, Kavli Neuroscience Discovery Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Richard H Roth
- Department of Neuroscience, Kavli Neuroscience Discovery Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Robert H Cudmore
- Department of Neuroscience, Kavli Neuroscience Discovery Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Richard L Huganir
- Department of Neuroscience, Kavli Neuroscience Discovery Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
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9
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Müller R. Bioinspiration from bats and new paradigms for autonomy in natural environments. BIOINSPIRATION & BIOMIMETICS 2024; 19:033001. [PMID: 38452384 DOI: 10.1088/1748-3190/ad311e] [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: 12/02/2023] [Accepted: 03/07/2024] [Indexed: 03/09/2024]
Abstract
Achieving autonomous operation in complex natural environment remains an unsolved challenge. Conventional engineering approaches to this problem have focused on collecting large amounts of sensory data that are used to create detailed digital models of the environment. However, this only postpones solving the challenge of identifying the relevant sensory information and linking it to action control to the domain of the digital world model. Furthermore, it imposes high demands in terms of computing power and introduces large processing latencies that hamper autonomous real-time performance. Certain species of bats that are able to navigate and hunt their prey in dense vegetation could be a biological model system for an alternative approach to addressing the fundamental issues associated with autonomy in complex natural environments. Bats navigating in dense vegetation rely on clutter echoes, i.e. signals that consist of unresolved contributions from many scatters. Yet, the animals are able to extract the relevant information from these input signals with brains that are often less than 1 g in mass. Pilot results indicate that information relevant to location identification and passageway finding can be directly obtained from clutter echoes, opening up the possibility that the bats' skill can be replicated in man-made autonomous systems.
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Affiliation(s)
- Rolf Müller
- Department of Mechanical Engineering, Virginia Tech, Blacksburg, VA 24061, United States of America
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10
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Golmohammadi M, Mahmoudian M, Hasan EK, Alshahrani SH, Romero-Parra RM, Malviya J, Hjazi A, Najm MAA, Almulla AF, Zamanian MY, Kadkhodaei M, Mousavi N. Neuroprotective effects of riluzole in Alzheimer's disease: A comprehensive review. Fundam Clin Pharmacol 2024; 38:225-237. [PMID: 37753585 DOI: 10.1111/fcp.12955] [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: 06/13/2023] [Revised: 08/18/2023] [Accepted: 08/24/2023] [Indexed: 09/28/2023]
Abstract
BACKGROUND Despite several hundred clinical trials of drugs that initially showed promise, there has been limited clinical improvement in Alzheimer's disease (AD). This may be attributed to the existence of at least 25 abnormal cellular pathways that underlie the disease. It is improbable for a single drug to address all or most of these pathways, thus even drugs that show promise when administered alone are unlikely to produce significant results. According to previous studies, eight drugs, namely, dantrolene, erythropoietin, lithium, memantine, minocycline, piracetam, riluzole, and silymarin, have been found to target multiple pathways that are involved in the development of AD. Among these drugs, riluzole is currently indicated for the treatment of medical conditions in both adult patients and children and has gained increased attention from scientists due to its potential in the excitotoxic hypothesis of neurodegenerative diseases. OBJECTIVE The aim of this study was to investigate the effects of drugs on AD based on cellular and molecular mechanisms. METHODS The literature search for this study utilized the Scopus, ScienceDirect, PubMed, and Google Scholar databases to identify relevant articles. RESULTS Riluzole exerts its effects in AD through diverse pathways including the inhibition of voltage-dependent sodium and calcium channels, blocking AMPA and NMDA receptors and inhibiting the release of glutamic acid release and stimulation of EAAT1-EAAT2. CONCLUSION In this review article, we aimed to review the neuroprotective properties of riluzole, a glutamate modulator, in AD, which could benefit patients with the disease.
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Affiliation(s)
- Maryam Golmohammadi
- School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | | | | | | | | | - Jitendra Malviya
- Department of Life Sciences and Biological Sciences, IES University, Bhopal, Madhya Pradesh, India
| | - Ahmed Hjazi
- Department of Medical Laboratory Sciences, College of Applied Medical Sciences, Prince Sattam bin Abdulaziz University, Al-Kharj, Saudi Arabia
| | - Mazin A A Najm
- Pharmaceutical Chemistry Department, College of Pharmacy, Al-Ayen University, Thi-Qar, Iraq
| | - Abbas F Almulla
- Medical Laboratory Technology Department, College of Medical Technology, The Islamic University, Najaf, Iraq
| | - Mohammad Yasin Zamanian
- Neurophysiology Research Center, Hamadan University of Medical Sciences, Hamadan, Iran
- Department of Pharmacology and Toxicology, School of Pharmacy, Hamadan University of Medical Sciences, Hamadan, Iran
| | - Mona Kadkhodaei
- Department of Surgery, Lorestan University of Medical Sciences, Khorramabad, Iran
| | - Nazanin Mousavi
- Department of Psychology, Imam Khomeini International University, Qazvin, Iran
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11
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Kim D, Park P, Li X, Wong Campos JD, Tian H, Moult EM, Grimm JB, Lavis L, Cohen AE. Mapping memories: pulse-chase labeling reveals AMPA receptor dynamics during memory formation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.26.541296. [PMID: 37292614 PMCID: PMC10246012 DOI: 10.1101/2023.05.26.541296] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
A tool to map changes in synaptic strength during a defined time window could provide powerful insights into the mechanisms governing learning and memory. We developed a technique, Extracellular Protein Surface Labeling in Neurons (EPSILON), to map α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) insertion in vivo by pulse-chase labeling of surface AMPARs with membrane-impermeable dyes. This approach allows for single-synapse resolution maps of plasticity in genetically targeted neurons during memory formation. We investigated the relationship between synapse-level and cell-level memory encodings by mapping synaptic plasticity and cFos expression in hippocampal CA1 pyramidal cells upon contextual fear conditioning (CFC). We observed a strong correlation between synaptic plasticity and cFos expression, suggesting a synaptic mechanism for the association of cFos expression with memory engrams. The EPSILON technique is a useful tool for mapping synaptic plasticity and may be extended to investigate trafficking of other transmembrane proteins.
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Affiliation(s)
- Doyeon Kim
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Pojeong Park
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Xiuyuan Li
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - J David Wong Campos
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - He Tian
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Eric M Moult
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Jonathan B Grimm
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA
| | - Luke Lavis
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA
| | - Adam E Cohen
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- Department of Physics, Harvard University, Cambridge, MA, USA
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12
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Chandra S, Chatterjee R, Olmsted ZT, Mukherjee A, Paluh JL. Axonal transport during injury on a theoretical axon. Front Cell Neurosci 2023; 17:1215945. [PMID: 37636588 PMCID: PMC10450981 DOI: 10.3389/fncel.2023.1215945] [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: 05/02/2023] [Accepted: 07/12/2023] [Indexed: 08/29/2023] Open
Abstract
Neurodevelopment, plasticity, and cognition are integral with functional directional transport in neuronal axons that occurs along a unique network of discontinuous polar microtubule (MT) bundles. Axonopathies are caused by brain trauma and genetic diseases that perturb or disrupt the axon MT infrastructure and, with it, the dynamic interplay of motor proteins and cargo essential for axonal maintenance and neuronal signaling. The inability to visualize and quantify normal and altered nanoscale spatio-temporal dynamic transport events prevents a full mechanistic understanding of injury, disease progression, and recovery. To address this gap, we generated DyNAMO, a Dynamic Nanoscale Axonal MT Organization model, which is a biologically realistic theoretical axon framework. We use DyNAMO to experimentally simulate multi-kinesin traffic response to focused or distributed tractable injury parameters, which are MT network perturbations affecting MT lengths and multi-MT staggering. We track kinesins with different motility and processivity, as well as their influx rates, in-transit dissociation and reassociation from inter-MT reservoirs, progression, and quantify and spatially represent motor output ratios. DyNAMO demonstrates, in detail, the complex interplay of mixed motor types, crowding, kinesin off/on dissociation and reassociation, and injury consequences of forced intermingling. Stalled forward progression with different injury states is seen as persistent dynamicity of kinesins transiting between MTs and inter-MT reservoirs. DyNAMO analysis provides novel insights and quantification of axonal injury scenarios, including local injury-affected ATP levels, as well as relates these to influences on signaling outputs, including patterns of gating, waves, and pattern switching. The DyNAMO model significantly expands the network of heuristic and mathematical analysis of neuronal functions relevant to axonopathies, diagnostics, and treatment strategies.
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Affiliation(s)
- Soumyadeep Chandra
- Electrical and Computer Science Engineering, Purdue University, West Lafayette, IN, United States
| | - Rounak Chatterjee
- Department of Electronics, Electrical and Systems Engineering, University of Birmingham, Birmingham, United Kingdom
| | - Zachary T. Olmsted
- Nanobioscience, College of Nanoscale Science and Engineering, State University of New York Polytechnic Institute, Albany, NY, United States
- Department of Neurosurgery, Ronald Reagan UCLA Medical Center, University of California, Los Angeles, Los Angeles, CA, United States
| | - Amitava Mukherjee
- Nanobioscience, College of Nanoscale Science and Engineering, State University of New York Polytechnic Institute, Albany, NY, United States
- School of Computing, Amrita Vishwa Vidyapeetham (University), Kollam, Kerala, India
| | - Janet L. Paluh
- Nanobioscience, College of Nanoscale Science and Engineering, State University of New York Polytechnic Institute, Albany, NY, United States
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13
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Gebicke-Haerter PJ. The computational power of the human brain. Front Cell Neurosci 2023; 17:1220030. [PMID: 37608987 PMCID: PMC10441807 DOI: 10.3389/fncel.2023.1220030] [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: 05/19/2023] [Accepted: 07/05/2023] [Indexed: 08/24/2023] Open
Abstract
At the end of the 20th century, analog systems in computer science have been widely replaced by digital systems due to their higher computing power. Nevertheless, the question keeps being intriguing until now: is the brain analog or digital? Initially, the latter has been favored, considering it as a Turing machine that works like a digital computer. However, more recently, digital and analog processes have been combined to implant human behavior in robots, endowing them with artificial intelligence (AI). Therefore, we think it is timely to compare mathematical models with the biology of computation in the brain. To this end, digital and analog processes clearly identified in cellular and molecular interactions in the Central Nervous System are highlighted. But above that, we try to pinpoint reasons distinguishing in silico computation from salient features of biological computation. First, genuinely analog information processing has been observed in electrical synapses and through gap junctions, the latter both in neurons and astrocytes. Apparently opposed to that, neuronal action potentials (APs) or spikes represent clearly digital events, like the yes/no or 1/0 of a Turing machine. However, spikes are rarely uniform, but can vary in amplitude and widths, which has significant, differential effects on transmitter release at the presynaptic terminal, where notwithstanding the quantal (vesicular) release itself is digital. Conversely, at the dendritic site of the postsynaptic neuron, there are numerous analog events of computation. Moreover, synaptic transmission of information is not only neuronal, but heavily influenced by astrocytes tightly ensheathing the majority of synapses in brain (tripartite synapse). At least at this point, LTP and LTD modifying synaptic plasticity and believed to induce short and long-term memory processes including consolidation (equivalent to RAM and ROM in electronic devices) have to be discussed. The present knowledge of how the brain stores and retrieves memories includes a variety of options (e.g., neuronal network oscillations, engram cells, astrocytic syncytium). Also epigenetic features play crucial roles in memory formation and its consolidation, which necessarily guides to molecular events like gene transcription and translation. In conclusion, brain computation is not only digital or analog, or a combination of both, but encompasses features in parallel, and of higher orders of complexity.
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Affiliation(s)
- Peter J. Gebicke-Haerter
- Institute of Psychopharmacology, Central Institute of Mental Health, Faculty of Medicine, University of Heidelberg, Mannheim, Germany
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14
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Frady EP, Kleyko D, Sommer FT. Variable Binding for Sparse Distributed Representations: Theory and Applications. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2023; 34:2191-2204. [PMID: 34478381 DOI: 10.1109/tnnls.2021.3105949] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Variable binding is a cornerstone of symbolic reasoning and cognition. But how binding can be implemented in connectionist models has puzzled neuroscientists, cognitive psychologists, and neural network researchers for many decades. One type of connectionist model that naturally includes a binding operation is vector symbolic architectures (VSAs). In contrast to other proposals for variable binding, the binding operation in VSAs is dimensionality-preserving, which enables representing complex hierarchical data structures, such as trees, while avoiding a combinatoric expansion of dimensionality. Classical VSAs encode symbols by dense randomized vectors, in which information is distributed throughout the entire neuron population. By contrast, in the brain, features are encoded more locally, by the activity of single neurons or small groups of neurons, often forming sparse vectors of neural activation. Following Laiho et al. (2015), we explore symbolic reasoning with a special case of sparse distributed representations. Using techniques from compressed sensing, we first show that variable binding in classical VSAs is mathematically equivalent to tensor product binding between sparse feature vectors, another well-known binding operation which increases dimensionality. This theoretical result motivates us to study two dimensionality-preserving binding methods that include a reduction of the tensor matrix into a single sparse vector. One binding method for general sparse vectors uses random projections, the other, block-local circular convolution, is defined for sparse vectors with block structure, sparse block-codes. Our experiments reveal that block-local circular convolution binding has ideal properties, whereas random projection based binding also works, but is lossy. We demonstrate in example applications that a VSA with block-local circular convolution and sparse block-codes reaches similar performance as classical VSAs. Finally, we discuss our results in the context of neuroscience and neural networks.
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15
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Lube AJ, Ma X, Carlson BA. Spike timing-dependent plasticity alters electrosensory neuron synaptic strength in vitro but does not consistently predict changes in sensory tuning in vivo. J Neurophysiol 2023; 129:1127-1144. [PMID: 37073981 PMCID: PMC10151048 DOI: 10.1152/jn.00498.2022] [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: 12/12/2022] [Revised: 04/12/2023] [Accepted: 04/13/2023] [Indexed: 04/20/2023] Open
Abstract
How do sensory systems optimize detection of behaviorally relevant stimuli when the sensory environment is constantly changing? We addressed the role of spike timing-dependent plasticity (STDP) in driving changes in synaptic strength in a sensory pathway and whether those changes in synaptic strength could alter sensory tuning. It is challenging to precisely control temporal patterns of synaptic activity in vivo and replicate those patterns in vitro in behaviorally relevant ways. This makes it difficult to make connections between STDP-induced changes in synaptic physiology and plasticity in sensory systems. Using the mormyrid species Brevimyrus niger and Brienomyrus brachyistius, which produce electric organ discharges for electrolocation and communication, we can precisely control the timing of synaptic input in vivo and replicate these same temporal patterns of synaptic input in vitro. In central electrosensory neurons in the electric communication pathway, using whole cell intracellular recordings in vitro, we paired presynaptic input with postsynaptic spiking at different delays. Using whole cell intracellular recordings in awake, behaving fish, we paired sensory stimulation with postsynaptic spiking using the same delays. We found that Hebbian STDP predictably alters sensory tuning in vitro and is mediated by NMDA receptors. However, the change in synaptic responses induced by sensory stimulation in vivo did not adhere to the direction predicted by the STDP observed in vitro. Further analysis suggests that this difference is influenced by polysynaptic activity, including inhibitory interneurons. Our findings suggest that STDP rules operating at identified synapses may not drive predictable changes in sensory responses at the circuit level.NEW & NOTEWORTHY We replicated behaviorally relevant temporal patterns of synaptic activity in vitro and used the same patterns during sensory stimulation in vivo. There was a Hebbian spike timing-dependent plasticity (STDP) pattern in vitro, but sensory responses in vivo did not shift according to STDP predictions. Analysis suggests that this disparity is influenced by differences in polysynaptic activity, including inhibitory interneurons. These results suggest that STDP rules at synapses in vitro do not necessarily apply to circuits in vivo.
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Affiliation(s)
- Adalee J Lube
- Department of Biology, Washington University in St. Louis, St. Louis, Missouri, United States
| | - Xiaofeng Ma
- Department of Biology, Washington University in St. Louis, St. Louis, Missouri, United States
| | - Bruce A Carlson
- Department of Biology, Washington University in St. Louis, St. Louis, Missouri, United States
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16
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Al-Horani RA. Riluzole and its prodrugs for the treatment of Alzheimer's disease. Pharm Pat Anal 2023; 12:79-85. [PMID: 37140357 PMCID: PMC10318568 DOI: 10.4155/ppa-2023-0001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2023] [Accepted: 03/20/2023] [Indexed: 05/05/2023]
Abstract
Current medications for Alzheimer's disease help manage symptoms and behavioral problems. Nevertheless, they do not slow the progression of cognitive decline or dementia. A potential approach for treating Alzheimer's disease is to target neurons that are sensitive to disease pathobiology such as glutamatergic neurons. Several patents disclosed methods for treating Alzheimer's disease by administering riluzole or its prodrugs. Clinical trials revealed that 6 months treatment using riluzole or troriluzole is associated with a slower decline in the tomographic measures of the positron emissions of cerebral glucose metabolism in Alzheimer's patients. The proposed strategy claims to prevent and/or slow the cognitive decline of Alzheimer's patients and to enhance global functioning. These claims may also pave the way for other glutamate modulators to be used for Alzheimer's disease.
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Affiliation(s)
- Rami A Al-Horani
- Division of Basic Pharmaceutical Sciences, College of Pharmacy, Xavier University of Louisiana, New Orleans, LA 70125, USA
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17
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KASAI H. Unraveling the mysteries of dendritic spine dynamics: Five key principles shaping memory and cognition. PROCEEDINGS OF THE JAPAN ACADEMY. SERIES B, PHYSICAL AND BIOLOGICAL SCIENCES 2023; 99:254-305. [PMID: 37821392 PMCID: PMC10749395 DOI: 10.2183/pjab.99.018] [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: 05/13/2023] [Accepted: 07/11/2023] [Indexed: 10/13/2023]
Abstract
Recent research extends our understanding of brain processes beyond just action potentials and chemical transmissions within neural circuits, emphasizing the mechanical forces generated by excitatory synapses on dendritic spines to modulate presynaptic function. From in vivo and in vitro studies, we outline five central principles of synaptic mechanics in brain function: P1: Stability - Underpinning the integral relationship between the structure and function of the spine synapses. P2: Extrinsic dynamics - Highlighting synapse-selective structural plasticity which plays a crucial role in Hebbian associative learning, distinct from pathway-selective long-term potentiation (LTP) and depression (LTD). P3: Neuromodulation - Analyzing the role of G-protein-coupled receptors, particularly dopamine receptors, in time-sensitive modulation of associative learning frameworks such as Pavlovian classical conditioning and Thorndike's reinforcement learning (RL). P4: Instability - Addressing the intrinsic dynamics crucial to memory management during continual learning, spotlighting their role in "spine dysgenesis" associated with mental disorders. P5: Mechanics - Exploring how synaptic mechanics influence both sides of synapses to establish structural traces of short- and long-term memory, thereby aiding the integration of mental functions. We also delve into the historical background and foresee impending challenges.
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Affiliation(s)
- Haruo KASAI
- International Research Center for Neurointelligence (WPI-IRCN), UTIAS, The University of Tokyo, Bunkyo-ku, Tokyo, Japan
- Laboratory of Structural Physiology, Center for Disease Biology and Integrative Medicine, Faculty of Medicine, The University of Tokyo, Bunkyo-ku, Tokyo, Japan
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18
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Hopkins M, Fil J, Jones EG, Furber S. BitBrain and Sparse Binary Coincidence (SBC) memories: Fast, robust learning and inference for neuromorphic architectures. Front Neuroinform 2023; 17:1125844. [PMID: 37025552 PMCID: PMC10071999 DOI: 10.3389/fninf.2023.1125844] [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: 12/16/2022] [Accepted: 03/03/2023] [Indexed: 04/08/2023] Open
Abstract
We present an innovative working mechanism (the SBC memory) and surrounding infrastructure (BitBrain) based upon a novel synthesis of ideas from sparse coding, computational neuroscience and information theory that enables fast and adaptive learning and accurate, robust inference. The mechanism is designed to be implemented efficiently on current and future neuromorphic devices as well as on more conventional CPU and memory architectures. An example implementation on the SpiNNaker neuromorphic platform has been developed and initial results are presented. The SBC memory stores coincidences between features detected in class examples in a training set, and infers the class of a previously unseen test example by identifying the class with which it shares the highest number of feature coincidences. A number of SBC memories may be combined in a BitBrain to increase the diversity of the contributing feature coincidences. The resulting inference mechanism is shown to have excellent classification performance on benchmarks such as MNIST and EMNIST, achieving classification accuracy with single-pass learning approaching that of state-of-the-art deep networks with much larger tuneable parameter spaces and much higher training costs. It can also be made very robust to noise. BitBrain is designed to be very efficient in training and inference on both conventional and neuromorphic architectures. It provides a unique combination of single-pass, single-shot and continuous supervised learning; following a very simple unsupervised phase. Accurate classification inference that is very robust against imperfect inputs has been demonstrated. These contributions make it uniquely well-suited for edge and IoT applications.
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19
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Nebeling FC, Poll S, Justus LC, Steffen J, Keppler K, Mittag M, Fuhrmann M. Microglial motility is modulated by neuronal activity and correlates with dendritic spine plasticity in the hippocampus of awake mice. eLife 2023; 12:83176. [PMID: 36749020 PMCID: PMC9946443 DOI: 10.7554/elife.83176] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 02/03/2023] [Indexed: 02/08/2023] Open
Abstract
Microglia, the resident immune cells of the brain, play a complex role in health and disease. They actively survey the brain parenchyma by physically interacting with other cells and structurally shaping the brain. Yet, the mechanisms underlying microglial motility and significance for synapse stability, especially in the hippocampus during adulthood, remain widely unresolved. Here, we investigated the effect of neuronal activity on microglial motility and the implications for the formation and survival of dendritic spines on hippocampal CA1 neurons in vivo. We used repetitive two-photon in vivo imaging in the hippocampus of awake and anesthetized mice to simultaneously study the motility of microglia and their interaction with dendritic spines. We found that CA3 to CA1 input is sufficient to modulate microglial process motility. Simultaneously, more dendritic spines emerged in mice after awake compared to anesthetized imaging. Interestingly, the rate of microglial contacts with individual dendritic spines and dendrites was associated with the stability, removal, and emergence of dendritic spines. These results suggest that microglia might sense neuronal activity via neurotransmitter release and actively participate in synaptic rewiring of the hippocampal neural network during adulthood. Further, this study has profound relevance for hippocampal learning and memory processes.
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Affiliation(s)
| | - Stefanie Poll
- Neuroimmunology and Imaging Group, German Center for Neurodegenerative DiseasesBonnGermany
| | - Lena Christine Justus
- Neuroimmunology and Imaging Group, German Center for Neurodegenerative DiseasesBonnGermany
| | - Julia Steffen
- Neuroimmunology and Imaging Group, German Center for Neurodegenerative DiseasesBonnGermany
| | - Kevin Keppler
- Light Microscopy Facility, German Center for Neurodegenerative DiseasesBonnGermany
| | - Manuel Mittag
- Neuroimmunology and Imaging Group, German Center for Neurodegenerative DiseasesBonnGermany
| | - Martin Fuhrmann
- Neuroimmunology and Imaging Group, German Center for Neurodegenerative DiseasesBonnGermany
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20
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Rindner DJ, Proddutur A, Lur G. Cell-type-specific integration of feedforward and feedback synaptic inputs in the posterior parietal cortex. Neuron 2022; 110:3760-3773.e5. [PMID: 36087582 PMCID: PMC9671855 DOI: 10.1016/j.neuron.2022.08.019] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 07/19/2022] [Accepted: 08/16/2022] [Indexed: 12/15/2022]
Abstract
The integration of feedforward (sensory) and feedback (top-down) neuronal signals is a principal function of the neocortex. Yet, we have limited insight into how these information streams are combined by individual neurons. Using a two-color optogenetic strategy, we found that layer 5 pyramidal neurons in the posterior parietal cortex receive monosynaptic dual innervation, combining sensory inputs with top-down signals. Subclasses of layer 5 pyramidal neurons integrated these synapses with distinct temporal dynamics. Specifically, regular spiking cells exhibited supralinear enhancement of delayed-but not coincident-inputs, while intrinsic burst-firing neurons selectively boosted coincident synaptic events. These subthreshold integration characteristics translated to a nonlinear summation of action potential firing. Complementing electrophysiology with computational modeling, we found that distinct integration profiles arose from a cell-type-specific interaction of ionic mechanisms and feedforward inhibition. These data provide insight into the cellular properties that guide the nonlinear interaction of distinct long-range afferents in the neocortex.
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Affiliation(s)
- Daniel J Rindner
- Department of Neurobiology and Behavior, University of California, Irvine, 1215 McGaugh Hall, Irvine, CA 92697, USA
| | - Archana Proddutur
- Department of Neurobiology and Behavior, University of California, Irvine, 1215 McGaugh Hall, Irvine, CA 92697, USA
| | - Gyorgy Lur
- Department of Neurobiology and Behavior, University of California, Irvine, 1215 McGaugh Hall, Irvine, CA 92697, USA.
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21
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Sohn J, Suzuki M, Youssef M, Hatada S, Larkum ME, Kawaguchi Y, Kubota Y. Presynaptic supervision of cortical spine dynamics in motor learning. SCIENCE ADVANCES 2022; 8:eabm0531. [PMID: 35895812 PMCID: PMC9328689 DOI: 10.1126/sciadv.abm0531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Accepted: 06/09/2022] [Indexed: 06/15/2023]
Abstract
In mammalian neocortex, learning triggers the formation and turnover of new postsynaptic spines on pyramidal cell dendrites. However, the biological principles of spine reorganization during learning remain elusive because the identity of their presynaptic neuronal partners is unknown. Here, we show that two presynaptic neural circuits supervise distinct programs of spine dynamics to execute learning. We imaged spine dynamics in motor cortex during learning and performed post hoc identification of their afferent presynaptic neurons. New spines that appeared during learning formed small transient contacts with corticocortical neurons that were eliminated on skill acquisition. In contrast, persistent spines with axons from thalamic neurons were formed and enlarged. These results suggest that pyramidal cell dendrites in motor cortex use a neural circuit division of labor during skill learning, with dynamic teaching contacts from top-down intracortical axons followed by synaptic memory formation driven by thalamic axons. Dual spine supervision may govern diverse skill learning in the neocortex.
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Affiliation(s)
- Jaerin Sohn
- Division of Cerebral Circuitry, National Institute for Physiological Sciences (NIPS), Okazaki 444-8787, Japan
- Section of Electron Microscopy, Supportive Center for Brain Research, National Institute for Physiological Sciences (NIPS), Okazaki 444-8787, Japan
| | - Mototaka Suzuki
- Neurocure Center for Excellence, Charité Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - Mohammed Youssef
- Division of Cerebral Circuitry, National Institute for Physiological Sciences (NIPS), Okazaki 444-8787, Japan
- Department of Animal Physiology, Faculty of Veterinary Medicine, South Valley University, Qena 83523, Egypt
| | - Sayuri Hatada
- Division of Cerebral Circuitry, National Institute for Physiological Sciences (NIPS), Okazaki 444-8787, Japan
| | - Matthew E. Larkum
- Neurocure Center for Excellence, Charité Universitätsmedizin Berlin, 10117 Berlin, Germany
- Institute of Biology, Humboldt University of Berlin, 10117 Berlin, Germany
| | - Yasuo Kawaguchi
- Division of Cerebral Circuitry, National Institute for Physiological Sciences (NIPS), Okazaki 444-8787, Japan
- Department of Physiological Sciences, The Graduate University for Advanced Studies (SOKENDAI), Okazaki 444-8787, Japan
- Brain Science Institute, Tamagawa University, Machida, Tokyo 194-8610, Japan
| | - Yoshiyuki Kubota
- Division of Cerebral Circuitry, National Institute for Physiological Sciences (NIPS), Okazaki 444-8787, Japan
- Section of Electron Microscopy, Supportive Center for Brain Research, National Institute for Physiological Sciences (NIPS), Okazaki 444-8787, Japan
- Department of Physiological Sciences, The Graduate University for Advanced Studies (SOKENDAI), Okazaki 444-8787, Japan
- Support Unit for Electron Microscopy Techniques, Research Resources Division, RIKEN Center for Brain Science, Wako 351-0198, Japan
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22
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D'Angelo E, Jirsa V. The quest for multiscale brain modeling. Trends Neurosci 2022; 45:777-790. [PMID: 35906100 DOI: 10.1016/j.tins.2022.06.007] [Citation(s) in RCA: 40] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Revised: 05/20/2022] [Accepted: 06/21/2022] [Indexed: 01/07/2023]
Abstract
Addressing the multiscale organization of the brain, which is fundamental to the dynamic repertoire of the organ, remains challenging. In principle, it should be possible to model neurons and synapses in detail and then connect them into large neuronal assemblies to explain the relationship between microscopic phenomena, large-scale brain functions, and behavior. It is more difficult to infer neuronal functions from ensemble measurements such as those currently obtained with brain activity recordings. In this article we consider theories and strategies for combining bottom-up models, generated from principles of neuronal biophysics, with top-down models based on ensemble representations of network activity and on functional principles. These integrative approaches are hoped to provide effective multiscale simulations in virtual brains and neurorobots, and pave the way to future applications in medicine and information technologies.
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Affiliation(s)
- Egidio D'Angelo
- Department of Brain and Behavioral Sciences, University of Pavia, and Brain Connectivity Center, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Mondino Foundation, Pavia, Italy.
| | - Viktor Jirsa
- Institut National de la Santé et de la Recherche Médicale (INSERM) Unité 1106, Centre National de la Recherche Scientifique (CNRS), and University of Aix-Marseille, Marseille, France
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23
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Yamada R, Kuba H. Cellular Strategies for Frequency-Dependent Computation of Interaural Time Difference. Front Synaptic Neurosci 2022; 14:891740. [PMID: 35602551 PMCID: PMC9120351 DOI: 10.3389/fnsyn.2022.891740] [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: 03/08/2022] [Accepted: 04/04/2022] [Indexed: 11/13/2022] Open
Abstract
Binaural coincidence detection is the initial step in encoding interaural time differences (ITDs) for sound-source localization. In birds, neurons in the nucleus laminaris (NL) play a central role in this process. These neurons receive excitatory synaptic inputs on dendrites from both sides of the cochlear nucleus and compare their coincidences at the soma. The NL is tonotopically organized, and individual neurons receive a pattern of synaptic inputs that are specific to their tuning frequency. NL neurons differ in their dendritic morphology along the tonotopic axis; their length increases with lower tuning frequency. In addition, our series of studies have revealed several frequency-dependent refinements in the morphological and biophysical characteristics of NL neurons, such as the amount and subcellular distribution of ion channels and excitatory and inhibitory synapses, which enable the neurons to process the frequency-specific pattern of inputs appropriately and encode ITDs at each frequency band. In this review, we will summarize these refinements of NL neurons and their implications for the ITD coding. We will also discuss the similarities and differences between avian and mammalian coincidence detectors.
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24
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Larkum M. Are dendrites conceptually useful? Neuroscience 2022; 489:4-14. [DOI: 10.1016/j.neuroscience.2022.03.008] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Revised: 02/10/2022] [Accepted: 03/05/2022] [Indexed: 12/13/2022]
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25
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Larkum ME, Wu J, Duverdin SA, Gidon A. The guide to dendritic spikes of the mammalian cortex in vitro and in vivo. Neuroscience 2022; 489:15-33. [PMID: 35182699 DOI: 10.1016/j.neuroscience.2022.02.009] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Revised: 02/01/2022] [Accepted: 02/10/2022] [Indexed: 12/23/2022]
Abstract
Half a century since their discovery by Llinás and colleagues, dendritic spikes have been observed in various neurons in different brain regions, from the neocortex and cerebellum to the basal ganglia. Dendrites exhibit a terrifically diverse but stereotypical repertoire of spikes, sometimes specific to subregions of the dendrite. Despite their prevalence, we only have a glimpse into their role in the behaving animal. This article aims to survey the full range of dendritic spikes found in excitatory and inhibitory neurons, compare them in vivo versus in vitro, and discuss new studies describing dendritic spikes in the human cortex. We focus on dendritic spikes in neocortical and hippocampal neurons and present a roadmap to identify and understand the broader role of dendritic spikes in single-cell computation.
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Affiliation(s)
- Matthew E Larkum
- Institute for Biology, Humboldt-Universität zu Berlin, Berlin, Germany; NeuroCure Cluster, Charité - Universitätsmedizin Berlin, Germany
| | - Jiameng Wu
- Institute for Biology, Humboldt-Universität zu Berlin, Berlin, Germany; Einstein Center for Neurosciences Berlin, Berlin, Germany
| | - Sarah A Duverdin
- Institute for Biology, Humboldt-Universität zu Berlin, Berlin, Germany; Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Albert Gidon
- Institute for Biology, Humboldt-Universität zu Berlin, Berlin, Germany
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26
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Matthews DC, Mao X, Dowd K, Tsakanikas D, Jiang CS, Meuser C, Andrews RD, Lukic AS, Lee J, Hampilos N, Shafiian N, Sano M, David Mozley P, Fillit H, McEwen BS, Shungu DC, Pereira AC. Riluzole, a glutamate modulator, slows cerebral glucose metabolism decline in patients with Alzheimer's disease. Brain 2021; 144:3742-3755. [PMID: 34145880 PMCID: PMC8719848 DOI: 10.1093/brain/awab222] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Revised: 04/07/2021] [Accepted: 05/22/2021] [Indexed: 11/14/2022] Open
Abstract
Dysregulation of glutamatergic neural circuits has been implicated in a cycle of toxicity, believed among the neurobiological underpinning of Alzheimer's disease. Previously, we reported preclinical evidence that the glutamate modulator riluzole, which is FDA approved for the treatment of amyotrophic lateral sclerosis, has potential benefits on cognition, structural and molecular markers of ageing and Alzheimer's disease. The objective of this study was to evaluate in a pilot clinical trial, using neuroimaging biomarkers, the potential efficacy and safety of riluzole in patients with Alzheimer's disease as compared to placebo. A 6-month phase 2 double-blind, randomized, placebo-controlled study was conducted at two sites. Participants consisted of males and females, 50 to 95 years of age, with a clinical diagnosis of probable Alzheimer's disease, and Mini-Mental State Examination between 19 and 27. Ninety-four participants were screened, 50 participants who met inclusion criteria were randomly assigned to receive 50 mg riluzole (n = 26) or placebo (n = 24) twice a day. Twenty-two riluzole-treated and 20 placebo participants completed the study. Primary end points were baseline to 6 months changes in (i) cerebral glucose metabolism as measured with fluorodeoxyglucose-PET in prespecified regions of interest (hippocampus, posterior cingulate, precuneus, lateral temporal, inferior parietal, frontal); and (ii) changes in posterior cingulate levels of the neuronal viability marker N-acetylaspartate as measured with in vivo proton magnetic resonance spectroscopy. Secondary outcome measures were neuropsychological testing for correlation with neuroimaging biomarkers and in vivo measures of glutamate in posterior cingulate measured with magnetic resonance spectroscopy as a potential marker of target engagement. Measures of cerebral glucose metabolism, a well-established Alzheimer's disease biomarker and predictor of disease progression, declined significantly less in several prespecified regions of interest with the most robust effect in posterior cingulate, and effects in precuneus, lateral temporal, right hippocampus and frontal cortex in riluzole-treated participants in comparison to the placebo group. No group effect was found in measures of N-acetylaspartate levels. A positive correlation was observed between cognitive measures and regional cerebral glucose metabolism. A group × visit interaction was observed in glutamate levels in posterior cingulate, potentially suggesting engagement of glutamatergic system by riluzole. In vivo glutamate levels positively correlated with cognitive performance. These findings support our main primary hypothesis that cerebral glucose metabolism would be better preserved in the riluzole-treated group than in the placebo group and provide a rationale for more powered, longer duration studies of riluzole as a potential intervention for Alzheimer's disease.
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Affiliation(s)
| | - Xiangling Mao
- Department of Radiology, Weill Cornell Medicine, New York, NY 10021, USA
| | | | | | | | - Caroline Meuser
- Department of Psychiatry, Alzheimer's Disease Research Center, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | | | - Ana S Lukic
- ADM Diagnostics Inc., Northbrook, IL 60062, USA
| | - Jihyun Lee
- Department of Radiology, Weill Cornell Medicine, New York, NY 10021, USA
| | - Nicholas Hampilos
- Department of Radiology, Weill Cornell Medicine, New York, NY 10021, USA
| | - Neeva Shafiian
- Department of Neurology, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Mary Sano
- Department of Psychiatry, Alzheimer's Disease Research Center, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - P David Mozley
- Department of Radiology, Weill Cornell Medicine, New York, NY 10021, USA
| | - Howard Fillit
- Alzheimer's Drug Discovery Foundation, New York, NY 10019, USA
| | | | - Dikoma C Shungu
- Department of Radiology, Weill Cornell Medicine, New York, NY 10021, USA
| | - Ana C Pereira
- The Rockefeller University, New York, NY 10065, USA
- Department of Neurology, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
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Yamada R, Kuba H. Dendritic synapse geometry optimizes binaural computation in a sound localization circuit. SCIENCE ADVANCES 2021; 7:eabh0024. [PMID: 34818046 PMCID: PMC8612683 DOI: 10.1126/sciadv.abh0024] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Accepted: 10/05/2021] [Indexed: 06/13/2023]
Abstract
Clustering of synapses allows neurons to overcome attenuation of electrical signals at dendrites. However, we show in avian binaural coincidence detectors computing interaural time difference for sound localization that clustering of synapses rather promotes the dendritic attenuation but augments the intensity tolerance of the binaural computations. Using glutamate uncaging, we found in the neurons that synapses were clustered at distal dendritic branches. Modeling revealed that this strengthened sublinear integration within a dendritic tree but enabled the integration of signals from different trees when inputs grow stronger, preventing monoaural output and maintaining the dynamic range of binaural computation. The extent of this clustering differed according to dendritic length and frequency tuning of neurons, being most prominent for long dendrites and low-frequency tuning. This ensures binaural spatial hearing for wide intensity and frequency ranges, highlighting the importance of coupling of synapse geometry with dendritic morphology and input frequency in sensory signal processing.
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Gorman JC, Tufte OL, Miller AVR, DeBello WM, Peña JL, Fischer BJ. Diverse processing underlying frequency integration in midbrain neurons of barn owls. PLoS Comput Biol 2021; 17:e1009569. [PMID: 34762650 PMCID: PMC8610287 DOI: 10.1371/journal.pcbi.1009569] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Revised: 11/23/2021] [Accepted: 10/16/2021] [Indexed: 11/18/2022] Open
Abstract
Emergent response properties of sensory neurons depend on circuit connectivity and somatodendritic processing. Neurons of the barn owl’s external nucleus of the inferior colliculus (ICx) display emergence of spatial selectivity. These neurons use interaural time difference (ITD) as a cue for the horizontal direction of sound sources. ITD is detected by upstream brainstem neurons with narrow frequency tuning, resulting in spatially ambiguous responses. This spatial ambiguity is resolved by ICx neurons integrating inputs over frequency, a relevant processing in sound localization across species. Previous models have predicted that ICx neurons function as point neurons that linearly integrate inputs across frequency. However, the complex dendritic trees and spines of ICx neurons raises the question of whether this prediction is accurate. Data from in vivo intracellular recordings of ICx neurons were used to address this question. Results revealed diverse frequency integration properties, where some ICx neurons showed responses consistent with the point neuron hypothesis and others with nonlinear dendritic integration. Modeling showed that varied connectivity patterns and forms of dendritic processing may underlie observed ICx neurons’ frequency integration processing. These results corroborate the ability of neurons with complex dendritic trees to implement diverse linear and nonlinear integration of synaptic inputs, of relevance for adaptive coding and learning, and supporting a fundamental mechanism in sound localization. Neurons at higher stages of sensory pathways often display selectivity for properties of sensory stimuli that result from computations performed within the nervous system. These emergent response properties can be produced by patterns of neural connectivity and processing that occur within individual cells. Here we investigated whether neural connectivity and single-neuron computation may contribute to the emergence of spatial selectivity in auditory neurons in the barn owl’s midbrain. We used data from in vivo intracellular recordings to test the hypothesis from previous modeling work that these cells function as point neurons that perform a linear sum of their inputs in their subthreshold responses. Results indicate that while some neurons show responses consistent with the point neuron hypothesis, others match predictions of nonlinear integration, indicating a diversity of frequency integration properties across neurons. Modeling further showed that varied connectivity patterns and forms of single-neuron computation may underlie observed responses. These results demonstrate that neurons with complex morphologies may implement diverse integration of synaptic inputs, relevant for adaptive coding and learning.
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Affiliation(s)
- Julia C. Gorman
- Department of Mathematics, Seattle University, Seattle, Washington, United States of America
| | - Oliver L. Tufte
- Department of Mathematics, Seattle University, Seattle, Washington, United States of America
| | - Anna V. R. Miller
- Department of Mathematics, Seattle University, Seattle, Washington, United States of America
| | - William M. DeBello
- Center for Neuroscience, University of California - Davis, Davis, California, United States of America
| | - José L. Peña
- Dominick P Purpura Department of Neuroscience, Albert Einstein College of Medicine, New York, New York, United States of America
| | - Brian J. Fischer
- Department of Mathematics, Seattle University, Seattle, Washington, United States of America
- * E-mail:
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29
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Albarran E, Raissi A, Jáidar O, Shatz CJ, Ding JB. Enhancing motor learning by increasing the stability of newly formed dendritic spines in the motor cortex. Neuron 2021; 109:3298-3311.e4. [PMID: 34437845 DOI: 10.1016/j.neuron.2021.07.030] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Revised: 07/10/2021] [Accepted: 07/30/2021] [Indexed: 12/18/2022]
Abstract
Dendritic spine dynamics are thought to be substrates for motor learning and memory, and altered spine dynamics often lead to impaired performance. Here, we describe an exception to this rule by studying mice lacking paired immunoglobulin receptor B (PirB-/-). Pyramidal neuron dendrites in PirB-/- mice have increased spine formation rates and density. Surprisingly, PirB-/- mice learn a skilled reaching task faster than wild-type (WT) littermates. Furthermore, stabilization of learning-induced spines is elevated in PirB-/- mice. Mechanistically, single-spine uncaging experiments suggest that PirB is required for NMDA receptor (NMDAR)-dependent spine shrinkage. The degree of survival of newly formed spines correlates with performance, suggesting that increased spine stability is advantageous for learning. Acute inhibition of PirB function in M1 of adult WT mice increases the survival of learning-induced spines and enhances motor learning. These results demonstrate that there are limits on motor learning that can be lifted by manipulating PirB, even in adulthood.
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Affiliation(s)
- Eddy Albarran
- Neurosciences Graduate Program, Stanford University, Stanford, CA 94305, USA
| | - Aram Raissi
- Department of Biology, Stanford University, Stanford, CA 94305, USA
| | - Omar Jáidar
- Department of Neurosurgery, Stanford University, Stanford, CA 94305, USA; Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA 94305, USA
| | - Carla J Shatz
- Department of Biology, Stanford University, Stanford, CA 94305, USA; Department of Neurobiology, Stanford University, Stanford, CA 94305, USA; Stanford Bio-X, Stanford University, Stanford, CA 94305, USA.
| | - Jun B Ding
- Department of Neurosurgery, Stanford University, Stanford, CA 94305, USA; Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA 94305, USA; Stanford Bio-X, Stanford University, Stanford, CA 94305, USA.
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30
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Brandalise F, Carta S, Leone R, Helmchen F, Holtmaat A, Gerber U. Dendritic Branch-constrained N-Methyl-d-Aspartate Receptor-mediated Spikes Drive Synaptic Plasticity in Hippocampal CA3 Pyramidal Cells. Neuroscience 2021; 489:57-68. [PMID: 34634424 DOI: 10.1016/j.neuroscience.2021.10.002] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Revised: 09/27/2021] [Accepted: 10/03/2021] [Indexed: 10/20/2022]
Abstract
N-methyl-d-aspartate receptor-mediated ( spikes can be causally linked to the induction of synaptic long-term potentiation (LTP) in hippocampal and cortical pyramidal cells. However, it is unclear if they regulate plasticity at a local or global scale in the dendritic tree. Here, we used dendritic patch-clamp recordings and calcium imaging to investigate the integrative properties of single dendrites of hippocampal CA3 cells. We show that local hyperpolarization of a single dendritic segment prevents NMDA spikes, their associated calcium transients, as well as LTP in a branch-specific manner. This result provides direct, causal evidence that the single dendritic branch can operate as a functional unit in regulating CA3 pyramidal cell plasticity.
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Affiliation(s)
- Federico Brandalise
- Department of Basic Neurosciences and the Center for Neuroscience, Centre Médical Universitaire (CMU), University of Geneva, 1211 Geneva, Switzerland; Former affiliation(b).
| | - Stefano Carta
- Brain Research Institute and Neuroscience Center Zurich, University of Zurich, CH-8057 Zurich, Switzerland
| | - Roberta Leone
- Department of Basic Neurosciences and the Center for Neuroscience, Centre Médical Universitaire (CMU), University of Geneva, 1211 Geneva, Switzerland
| | - Fritjof Helmchen
- Brain Research Institute and Neuroscience Center Zurich, University of Zurich, CH-8057 Zurich, Switzerland
| | - Anthony Holtmaat
- Department of Basic Neurosciences and the Center for Neuroscience, Centre Médical Universitaire (CMU), University of Geneva, 1211 Geneva, Switzerland
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31
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Khanal P, Hotulainen P. Dendritic Spine Initiation in Brain Development, Learning and Diseases and Impact of BAR-Domain Proteins. Cells 2021; 10:cells10092392. [PMID: 34572042 PMCID: PMC8468246 DOI: 10.3390/cells10092392] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Revised: 09/08/2021] [Accepted: 09/09/2021] [Indexed: 02/08/2023] Open
Abstract
Dendritic spines are small, bulbous protrusions along neuronal dendrites where most of the excitatory synapses are located. Dendritic spine density in normal human brain increases rapidly before and after birth achieving the highest density around 2-8 years. Density decreases during adolescence, reaching a stable level in adulthood. The changes in dendritic spines are considered structural correlates for synaptic plasticity as well as the basis of experience-dependent remodeling of neuronal circuits. Alterations in spine density correspond to aberrant brain function observed in various neurodevelopmental and neuropsychiatric disorders. Dendritic spine initiation affects spine density. In this review, we discuss the importance of spine initiation in brain development, learning, and potential complications resulting from altered spine initiation in neurological diseases. Current literature shows that two Bin Amphiphysin Rvs (BAR) domain-containing proteins, MIM/Mtss1 and SrGAP3, are involved in spine initiation. We review existing literature and open databases to discuss whether other BAR-domain proteins could also take part in spine initiation. Finally, we discuss the potential molecular mechanisms on how BAR-domain proteins could regulate spine initiation.
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Affiliation(s)
- Pushpa Khanal
- Minerva Foundation Institute for Medical Research, Tukholmankatu 8, 00290 Helsinki, Finland;
- HiLIFE-Neuroscience Center, University of Helsinki, 00014 Helsinki, Finland
| | - Pirta Hotulainen
- Minerva Foundation Institute for Medical Research, Tukholmankatu 8, 00290 Helsinki, Finland;
- Correspondence:
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32
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Semyanov A, Verkhratsky A. Astrocytic processes: from tripartite synapses to the active milieu. Trends Neurosci 2021; 44:781-792. [PMID: 34479758 DOI: 10.1016/j.tins.2021.07.006] [Citation(s) in RCA: 114] [Impact Index Per Article: 38.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Revised: 07/09/2021] [Accepted: 07/20/2021] [Indexed: 12/16/2022]
Abstract
We define a new concept of 'active milieu' that unifies all components of nervous tissue (neuronal and glial compartments, extracellular space, extracellular matrix, and vasculature) into a dynamic information processing system. Within this framework, we focus on the role of astrocytic processes, classified into organelle-containing branches and organelle-free leaflets. We argue that astrocytic branches with emanating leaflets are homologous to dendritic shafts with spines. Within the active milieu, astrocytic processes are engaged in reciprocal interactions with neuronal compartments and communication with other cellular and non-cellular elements of the nervous tissue.
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Affiliation(s)
- Alexey Semyanov
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, 117997, Russia; Faculty of Biology, Moscow State University, Moscow, Russia; Sechenov First Moscow State Medical University, Moscow, Russia.
| | - Alexei Verkhratsky
- Sechenov First Moscow State Medical University, Moscow, Russia; Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK; Achucarro Center for Neuroscience, IKERBASQUE, Basque Foundation for Science, 48011 Bilbao, Spain; Department of Neurosciences, University of the Basque Country UPV/EHU and CIBERNED, Leioa, Spain.
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33
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Goetz L, Roth A, Häusser M. Active dendrites enable strong but sparse inputs to determine orientation selectivity. Proc Natl Acad Sci U S A 2021; 118:e2017339118. [PMID: 34301882 PMCID: PMC8325157 DOI: 10.1073/pnas.2017339118] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
The dendrites of neocortical pyramidal neurons are excitable. However, it is unknown how synaptic inputs engage nonlinear dendritic mechanisms during sensory processing in vivo, and how they in turn influence action potential output. Here, we provide a quantitative account of the relationship between synaptic inputs, nonlinear dendritic events, and action potential output. We developed a detailed pyramidal neuron model constrained by in vivo dendritic recordings. We drive this model with realistic input patterns constrained by sensory responses measured in vivo and connectivity measured in vitro. We show mechanistically that under realistic conditions, dendritic Na+ and NMDA spikes are the major determinants of neuronal output in vivo. We demonstrate that these dendritic spikes can be triggered by a surprisingly small number of strong synaptic inputs, in some cases even by single synapses. We predict that dendritic excitability allows the 1% strongest synaptic inputs of a neuron to control the tuning of its output. Active dendrites therefore allow smaller subcircuits consisting of only a few strongly connected neurons to achieve selectivity for specific sensory features.
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Affiliation(s)
- Lea Goetz
- Wolfson Institute for Biomedical Research, University College London, London WC1E 6BT, United Kingdom
| | - Arnd Roth
- Wolfson Institute for Biomedical Research, University College London, London WC1E 6BT, United Kingdom
| | - Michael Häusser
- Wolfson Institute for Biomedical Research, University College London, London WC1E 6BT, United Kingdom
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34
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Stuyt G, Godenzini L, Palmer LM. Local and Global Dynamics of Dendritic Activity in the Pyramidal Neuron. Neuroscience 2021; 489:176-184. [PMID: 34280492 DOI: 10.1016/j.neuroscience.2021.07.008] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2021] [Revised: 07/06/2021] [Accepted: 07/08/2021] [Indexed: 12/22/2022]
Abstract
There has been increasing interest in the measurement and comparison of activity across compartments of the pyramidal neuron. Dendritic activity can occur both locally, on a single dendritic segment, or globally, involving multiple compartments of the single neuron. Little is known about how these dendritic dynamics shape and contribute to information processing and behavior. Although it has been difficult to characterize local and global activity in vivo due to the technical challenge of simultaneously recording from the entire dendritic arbor and soma, the rise of calcium imaging has driven the increased feasibility and interest of these experiments. However, the distinction between local and global activity made by calcium imaging requires careful consideration. In this review we describe local and global activity, discuss the difficulties and caveats of this distinction, and present the evidence of local and global activity in information processing and behavior.
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Affiliation(s)
- George Stuyt
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, Victoria 3052, Australia
| | - Luca Godenzini
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, Victoria 3052, Australia
| | - Lucy M Palmer
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, Victoria 3052, Australia.
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35
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Mackwood O, Naumann LB, Sprekeler H. Learning excitatory-inhibitory neuronal assemblies in recurrent networks. eLife 2021; 10:59715. [PMID: 33900199 PMCID: PMC8075581 DOI: 10.7554/elife.59715] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2020] [Accepted: 03/03/2021] [Indexed: 12/22/2022] Open
Abstract
Understanding the connectivity observed in the brain and how it emerges from local plasticity rules is a grand challenge in modern neuroscience. In the primary visual cortex (V1) of mice, synapses between excitatory pyramidal neurons and inhibitory parvalbumin-expressing (PV) interneurons tend to be stronger for neurons that respond to similar stimulus features, although these neurons are not topographically arranged according to their stimulus preference. The presence of such excitatory-inhibitory (E/I) neuronal assemblies indicates a stimulus-specific form of feedback inhibition. Here, we show that activity-dependent synaptic plasticity on input and output synapses of PV interneurons generates a circuit structure that is consistent with mouse V1. Computational modeling reveals that both forms of plasticity must act in synergy to form the observed E/I assemblies. Once established, these assemblies produce a stimulus-specific competition between pyramidal neurons. Our model suggests that activity-dependent plasticity can refine inhibitory circuits to actively shape cortical computations.
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Affiliation(s)
- Owen Mackwood
- Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany.,Department for Electrical Engineering and Computer Science, Technische Universität Berlin, Berlin, Germany
| | - Laura B Naumann
- Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany.,Department for Electrical Engineering and Computer Science, Technische Universität Berlin, Berlin, Germany
| | - Henning Sprekeler
- Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany.,Department for Electrical Engineering and Computer Science, Technische Universität Berlin, Berlin, Germany
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36
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Neuronal Network Excitability in Alzheimer's Disease: The Puzzle of Similar versus Divergent Roles of Amyloid β and Tau. eNeuro 2021; 8:ENEURO.0418-20.2020. [PMID: 33741601 PMCID: PMC8174042 DOI: 10.1523/eneuro.0418-20.2020] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Revised: 12/02/2020] [Accepted: 12/18/2020] [Indexed: 12/12/2022] Open
Abstract
Alzheimer’s disease (AD) is the most frequent neurodegenerative disorder that commonly causes dementia in the elderly. Recent evidence indicates that network abnormalities, including hypersynchrony, altered oscillatory rhythmic activity, interneuron dysfunction, and synaptic depression, may be key mediators of cognitive decline in AD. In this review, we discuss characteristics of neuronal network excitability in AD, and the role of Aβ and tau in the induction of network hyperexcitability. Many patients harboring genetic mutations that lead to increased Aβ production suffer from seizures and epilepsy before the development of plaques. Similarly, pathologic accumulation of hyperphosphorylated tau has been associated with hyperexcitability in the hippocampus. We present common and divergent roles of tau and Aβ on neuronal hyperexcitability in AD, and hypotheses that could serve as a template for future experiments.
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37
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Anomalous Behavior Detection Framework Using HTM-Based Semantic Folding Technique. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2021; 2021:5585238. [PMID: 33790986 PMCID: PMC7987406 DOI: 10.1155/2021/5585238] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/23/2021] [Revised: 02/17/2021] [Accepted: 02/26/2021] [Indexed: 11/17/2022]
Abstract
Upon the working principles of the human neocortex, the Hierarchical Temporal Memory model has been developed which is a proposed theoretical framework for sequence learning. Both categorical and numerical types of data are handled by HTM. Semantic Folding Theory (SFT) is based on HTM to represent a data stream for processing in the form of sparse distributed representation (SDR). For natural language perception and production, SFT delivers a solid structural background for semantic evidence description to the fundamentals of the semantic foundation during the phase of language learning. Anomalies are the patterns from data streams that do not follow the expected behavior. Any stream of data patterns could have a number of anomaly types. In a data stream, a single pattern or combination of closely related patterns that diverges and deviates from standard, normal, or expected is called a static (spatial) anomaly. A temporal anomaly is a set of unexpected changes between patterns. When a change first appears, this is recorded as an anomaly. If this change looks a number of times, then it is set to a “new normal” and terminated as an anomaly. An HTM system detects the anomaly, and due to continuous learning nature, it quickly learns when they become the new normal. A robust anomalous behavior detection framework using HTM-based SFT for improving decision-making (SDR-ABDF/P2) is a proposed framework or model in this research. The researcher claims that the proposed model would be able to learn the order of several variables continuously in temporal sequences by using an unsupervised learning rule.
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38
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Daria VR, Castañares ML, Bachor HA. Spatio-temporal parameters for optical probing of neuronal activity. Biophys Rev 2021; 13:13-33. [PMID: 33747244 PMCID: PMC7930150 DOI: 10.1007/s12551-021-00780-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2020] [Accepted: 01/01/2021] [Indexed: 12/28/2022] Open
Abstract
The challenge to understand the complex neuronal circuit functions in the mammalian brain has brought about a revolution in light-based neurotechnologies and optogenetic tools. However, while recent seminal works have shown excellent insights on the processing of basic functions such as sensory perception, memory, and navigation, understanding more complex brain functions is still unattainable with current technologies. We are just scratching the surface, both literally and figuratively. Yet, the path towards fully understanding the brain is not totally uncertain. Recent rapid technological advancements have allowed us to analyze the processing of signals within dendritic arborizations of single neurons and within neuronal circuits. Understanding the circuit dynamics in the brain requires a good appreciation of the spatial and temporal properties of neuronal activity. Here, we assess the spatio-temporal parameters of neuronal responses and match them with suitable light-based neurotechnologies as well as photochemical and optogenetic tools. We focus on the spatial range that includes dendrites and certain brain regions (e.g., cortex and hippocampus) that constitute neuronal circuits. We also review some temporal characteristics of some proteins and ion channels responsible for certain neuronal functions. With the aid of the photochemical and optogenetic markers, we can use light to visualize the circuit dynamics of a functioning brain. The challenge to understand how the brain works continue to excite scientists as research questions begin to link macroscopic and microscopic units of brain circuits.
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Affiliation(s)
- Vincent R. Daria
- Research School of Physics, The Australian National University, Canberra, Australia
- John Curtin School of Medical Research, The Australian National University, Canberra, Australia
| | | | - Hans-A. Bachor
- Research School of Physics, The Australian National University, Canberra, Australia
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39
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Jensen TP, Kopach O, Reynolds JP, Savtchenko LP, Rusakov DA. Release probability increases towards distal dendrites boosting high-frequency signal transfer in the rodent hippocampus. eLife 2021; 10:e62588. [PMID: 33438578 PMCID: PMC7837677 DOI: 10.7554/elife.62588] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2020] [Accepted: 01/12/2021] [Indexed: 11/30/2022] Open
Abstract
Dendritic integration of synaptic inputs involves their increased electrotonic attenuation at distal dendrites, which can be counterbalanced by the increased synaptic receptor density. However, during network activity, the influence of individual synapses depends on their release fidelity, the dendritic distribution of which remains poorly understood. Here, we employed classical optical quantal analyses and a genetically encoded optical glutamate sensor in acute hippocampal slices of rats and mice to monitor glutamate release at CA3-CA1 synapses. We find that their release probability increases with greater distances from the soma. Similar-fidelity synapses tend to group together, whereas release probability shows no trends regarding the branch ends. Simulations with a realistic CA1 pyramidal cell hosting stochastic synapses suggest that the observed trends boost signal transfer fidelity, particularly at higher input frequencies. Because high-frequency bursting has been associated with learning, the release probability pattern we have found may play a key role in memory trace formation.
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Affiliation(s)
- Thomas P Jensen
- Queen Square UCL Institute of Neurology, University College LondonLondonUnited Kingdom
| | - Olga Kopach
- Queen Square UCL Institute of Neurology, University College LondonLondonUnited Kingdom
| | - James P Reynolds
- Queen Square UCL Institute of Neurology, University College LondonLondonUnited Kingdom
| | - Leonid P Savtchenko
- Queen Square UCL Institute of Neurology, University College LondonLondonUnited Kingdom
| | - Dmitri A Rusakov
- Queen Square UCL Institute of Neurology, University College LondonLondonUnited Kingdom
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40
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Gao PP, Graham JW, Zhou WL, Jang J, Angulo S, Dura-Bernal S, Hines M, Lytton WW, Antic SD. Local glutamate-mediated dendritic plateau potentials change the state of the cortical pyramidal neuron. J Neurophysiol 2021; 125:23-42. [PMID: 33085562 PMCID: PMC8087381 DOI: 10.1152/jn.00734.2019] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2019] [Revised: 10/21/2020] [Accepted: 10/21/2020] [Indexed: 01/08/2023] Open
Abstract
Dendritic spikes in thin dendritic branches (basal and oblique dendrites) are traditionally inferred from spikelets measured in the cell body. Here, we used laser-spot voltage-sensitive dye imaging in cortical pyramidal neurons (rat brain slices) to investigate the voltage waveforms of dendritic potentials occurring in response to spatially restricted glutamatergic inputs. Local dendritic potentials lasted 200-500 ms and propagated to the cell body, where they caused sustained 10- to 20-mV depolarizations. Plateau potentials propagating from dendrite to soma and action potentials propagating from soma to dendrite created complex voltage waveforms in the middle of the thin basal dendrite, comprised of local sodium spikelets, local plateau potentials, and backpropagating action potentials, superimposed on each other. Our model replicated these voltage waveforms across a gradient of glutamatergic stimulation intensities. The model then predicted that somatic input resistance (Rin) and membrane time constant (tau) may be reduced during dendritic plateau potential. We then tested these model predictions in real neurons and found that the model correctly predicted the direction of Rin and tau change but not the magnitude. In summary, dendritic plateau potentials occurring in basal and oblique branches put pyramidal neurons into an activated neuronal state ("prepared state"), characterized by depolarized membrane potential and smaller but faster membrane responses. The prepared state provides a time window of 200-500 ms, during which cortical neurons are particularly excitable and capable of following afferent inputs. At the network level, this predicts that sets of cells with simultaneous plateaus would provide cellular substrate for the formation of functional neuronal ensembles.NEW & NOTEWORTHY In cortical pyramidal neurons, we recorded glutamate-mediated dendritic plateau potentials with voltage imaging and created a computer model that recreated experimental measures from dendrite and cell body. Our model made new predictions, which were then tested in experiments. Plateau potentials profoundly change neuronal state: a plateau potential triggered in one basal dendrite depolarizes the soma and shortens membrane time constant, making the cell more susceptible to firing triggered by other afferent inputs.
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Affiliation(s)
- Peng P Gao
- Institute for Systems Genomics, UConn Health, Farmington, Connecticut
| | - Joseph W Graham
- Department of Physiology and Pharmacology, SUNY Downstate, Brooklyn, New York
| | - Wen-Liang Zhou
- Institute for Systems Genomics, UConn Health, Farmington, Connecticut
| | - Jinyoung Jang
- Institute for Systems Genomics, UConn Health, Farmington, Connecticut
| | - Sergio Angulo
- Department of Physiology and Pharmacology, SUNY Downstate, Brooklyn, New York
| | | | - Michael Hines
- Department of Neuroscience, Yale University, New Haven, Connecticut
| | - William W Lytton
- Department of Physiology and Pharmacology, SUNY Downstate, Brooklyn, New York
- Kings County Hospital, Brooklyn, New York
| | - Srdjan D Antic
- Institute for Systems Genomics, UConn Health, Farmington, Connecticut
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Marti Mengual U, Wybo WAM, Spierenburg LJE, Santello M, Senn W, Nevian T. Efficient Low-Pass Dendro-Somatic Coupling in the Apical Dendrite of Layer 5 Pyramidal Neurons in the Anterior Cingulate Cortex. J Neurosci 2020; 40:8799-8815. [PMID: 33046549 PMCID: PMC7659461 DOI: 10.1523/jneurosci.3028-19.2020] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2019] [Revised: 09/30/2020] [Accepted: 10/03/2020] [Indexed: 11/21/2022] Open
Abstract
Signal propagation in the dendrites of many neurons, including cortical pyramidal neurons in sensory cortex, is characterized by strong attenuation toward the soma. In contrast, using dual whole-cell recordings from the apical dendrite and soma of layer 5 (L5) pyramidal neurons in the anterior cingulate cortex (ACC) of adult male mice we found good coupling, particularly of slow subthreshold potentials like NMDA spikes or trains of EPSPs from dendrite to soma. Only the fastest EPSPs in the ACC were reduced to a similar degree as in primary somatosensory cortex, revealing differential low-pass filtering capabilities. Furthermore, L5 pyramidal neurons in the ACC did not exhibit dendritic Ca2+ spikes as prominently found in the apical dendrite of S1 (somatosensory cortex) pyramidal neurons. Fitting the experimental data to a NEURON model revealed that the specific distribution of Ileak, Iir, Im , and Ih was sufficient to explain the electrotonic dendritic structure causing a leaky distal dendritic compartment with correspondingly low input resistance and a compact perisomatic region, resulting in a decoupling of distal tuft branches from each other while at the same time efficiently connecting them to the soma. Our results give a biophysically plausible explanation of how a class of prefrontal cortical pyramidal neurons achieve efficient integration of subthreshold distal synaptic inputs compared with the same cell type in sensory cortices.SIGNIFICANCE STATEMENT Understanding cortical computation requires the understanding of its fundamental computational subunits. Layer 5 pyramidal neurons are the main output neurons of the cortex, integrating synaptic inputs across different cortical layers. Their elaborate dendritic tree receives, propagates, and transforms synaptic inputs into action potential output. We found good coupling of slow subthreshold potentials like NMDA spikes or trains of EPSPs from the distal apical dendrite to the soma in pyramidal neurons in the ACC, which was significantly better compared with S1. This suggests that frontal pyramidal neurons use a different integration scheme compared with the same cell type in somatosensory cortex, which has important implications for our understanding of information processing across different parts of the neocortex.
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Affiliation(s)
| | - Willem A M Wybo
- Department of Physiology, University of Bern, 3012 Bern, Switzerland
| | | | - Mirko Santello
- Department of Physiology, University of Bern, 3012 Bern, Switzerland
- Institute of Pharmacology and Toxicology, University of Zürich, 8057 Zürich, Switzerland
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, 8057 Zurich, Switzerland
| | - Walter Senn
- Department of Physiology, University of Bern, 3012 Bern, Switzerland
| | - Thomas Nevian
- Department of Physiology, University of Bern, 3012 Bern, Switzerland
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Geometry and the Organizational Principle of Spine Synapses along a Dendrite. eNeuro 2020; 7:ENEURO.0248-20.2020. [PMID: 33109633 PMCID: PMC7772515 DOI: 10.1523/eneuro.0248-20.2020] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Revised: 10/02/2020] [Accepted: 10/07/2020] [Indexed: 12/12/2022] Open
Abstract
Precise information on synapse organization in a dendrite is crucial to understanding the mechanisms underlying voltage integration and the variability in the strength of synaptic inputs across dendrites of different complex morphologies. Here, we used focused ion beam/scanning electron microscope (FIB/SEM) to image the dendritic spines of mice in the hippocampal CA1 region, CA3 region, somatosensory cortex, striatum, and cerebellum (CB). Our results show that the spine geometry and dimensions differ across neuronal cell types. Despite this difference, dendritic spines were organized in an orchestrated manner such that the postsynaptic density (PSD) area per unit length of dendrite scaled positively with the dendritic diameter in CA1 proximal stratum radiatum (PSR), cortex, and CB. The ratio of the PSD area to neck length was kept relatively uniform across dendrites of different diameters in CA1 PSR. Computer simulation suggests that a similar level of synaptic strength across different dendrites in CA1 PSR enables the effective transfer of synaptic inputs from the dendrites toward soma. Excitatory postsynaptic potentials (EPSPs), evoked at single spines by glutamate uncaging and recorded at the soma, show that the neck length is more influential than head width in regulating the EPSP magnitude at the soma. Our study describes thorough morphologic features and the organizational principles of dendritic spines in different brain regions.
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Zhu PK, Zheng WS, Zhang P, Jing M, Borden PM, Ali F, Guo K, Feng J, Marvin JS, Wang Y, Wan J, Gan L, Kwan AC, Lin L, Looger LL, Li Y, Zhang Y. Nanoscopic Visualization of Restricted Nonvolume Cholinergic and Monoaminergic Transmission with Genetically Encoded Sensors. NANO LETTERS 2020; 20:4073-4083. [PMID: 32396366 PMCID: PMC7519949 DOI: 10.1021/acs.nanolett.9b04877] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
How neuromodulatory transmitters diffuse into the extracellular space remains an unsolved fundamental biological question, despite wide acceptance of the volume transmission model. Here, we report development of a method combining genetically encoded fluorescent sensors with high-resolution imaging and analysis algorithms which permits the first direct visualization of neuromodulatory transmitter diffusion at various neuronal and non-neuronal cells. Our analysis reveals that acetylcholine and monoamines diffuse at individual release sites with a spread length constant of ∼0.75 μm. These transmitters employ varied numbers of release sites, and when spatially close-packed release sites coactivate they can spillover into larger subcellular areas. Our data indicate spatially restricted (i.e., nonvolume) neuromodulatory transmission to be a prominent intercellular communication mode, reshaping current thinking of control and precision of neuromodulation crucial for understanding behaviors and diseases.
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Affiliation(s)
- Paula K. Zhu
- State Key Laboratory of Membrane Biology and Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China
- Math, Engineering & Science Academy Class of 2020, Albemarle High School, Charlottesville, VA 22901
- Summer Secondary School Neurobiology Class of 2019, Harvard University, Cambridge, MA 02138
- Current address: Undergraduate Class of 2024, Harvard College, Cambridge, MA 02138
| | - W. Sharon Zheng
- Department of Pharmacology, University of Virginia School of Medicine, Charlottesville, VA 22908
- Department of Biomedical Engineering Class of 2021, University of Virginia School of Medicine, Charlottesville, VA 22908
| | - Peng Zhang
- Department of Pharmacology, University of Virginia School of Medicine, Charlottesville, VA 22908
| | - Miao Jing
- State Key Laboratory of Membrane Biology and Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China
- Chinese Institute for Brain Research, Beijing 100871, China
| | - Philip M. Borden
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147
- Current address: LifeEDIT, Research Triangle Park, NC 27709
| | - Farhan Ali
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06511
| | - Kaiming Guo
- Department of Pharmacology, University of Virginia School of Medicine, Charlottesville, VA 22908
- School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou 325035, China
| | - Jiesi Feng
- State Key Laboratory of Membrane Biology and Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China
| | - Jonathan S. Marvin
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147
| | - Yali Wang
- Department of Pharmacology, University of Virginia School of Medicine, Charlottesville, VA 22908
| | - Jinxia Wan
- State Key Laboratory of Membrane Biology and Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China
| | - Li Gan
- Helen and Robert Appel Alzheimer’s Disease Research Institute, Weill Cornell Medicine College, New York, NY 10065
| | - Alex C. Kwan
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06511
| | - Li Lin
- School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou 325035, China
| | - Loren L. Looger
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147
| | - Yulong Li
- State Key Laboratory of Membrane Biology and Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China
| | - Yajun Zhang
- State Key Laboratory of Membrane Biology and Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China
- Department of Pharmacology, University of Virginia School of Medicine, Charlottesville, VA 22908
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Poirazi P, Papoutsi A. Illuminating dendritic function with computational models. Nat Rev Neurosci 2020; 21:303-321. [PMID: 32393820 DOI: 10.1038/s41583-020-0301-7] [Citation(s) in RCA: 91] [Impact Index Per Article: 22.8] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/25/2020] [Indexed: 02/06/2023]
Abstract
Dendrites have always fascinated researchers: from the artistic drawings by Ramon y Cajal to the beautiful recordings of today, neuroscientists have been striving to unravel the mysteries of these structures. Theoretical work in the 1960s predicted important dendritic effects on neuronal processing, establishing computational modelling as a powerful technique for their investigation. Since then, modelling of dendrites has been instrumental in driving neuroscience research in a targeted manner, providing experimentally testable predictions that range from the subcellular level to the systems level, and their relevance extends to fields beyond neuroscience, such as machine learning and artificial intelligence. Validation of modelling predictions often requires - and drives - new technological advances, thus closing the loop with theory-driven experimentation that moves the field forward. This Review features the most important, to our understanding, contributions of modelling of dendritic computations, including those pending experimental verification, and highlights studies of successful interactions between the modelling and experimental neuroscience communities.
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Affiliation(s)
- Panayiota Poirazi
- Institute of Molecular Biology & Biotechnology, Foundation for Research & Technology - Hellas, Heraklion, Crete, Greece.
| | - Athanasia Papoutsi
- Institute of Molecular Biology & Biotechnology, Foundation for Research & Technology - Hellas, Heraklion, Crete, Greece
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45
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Moldwin T, Segev I. Perceptron Learning and Classification in a Modeled Cortical Pyramidal Cell. Front Comput Neurosci 2020; 14:33. [PMID: 32390819 PMCID: PMC7193948 DOI: 10.3389/fncom.2020.00033] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2019] [Accepted: 03/25/2020] [Indexed: 12/04/2022] Open
Abstract
The perceptron learning algorithm and its multiple-layer extension, the backpropagation algorithm, are the foundations of the present-day machine learning revolution. However, these algorithms utilize a highly simplified mathematical abstraction of a neuron; it is not clear to what extent real biophysical neurons with morphologically-extended non-linear dendritic trees and conductance-based synapses can realize perceptron-like learning. Here we implemented the perceptron learning algorithm in a realistic biophysical model of a layer 5 cortical pyramidal cell with a full complement of non-linear dendritic channels. We tested this biophysical perceptron (BP) on a classification task, where it needed to correctly binarily classify 100, 1,000, or 2,000 patterns, and a generalization task, where it was required to discriminate between two "noisy" patterns. We show that the BP performs these tasks with an accuracy comparable to that of the original perceptron, though the classification capacity of the apical tuft is somewhat limited. We concluded that cortical pyramidal neurons can act as powerful classification devices.
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Affiliation(s)
- Toviah Moldwin
- Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Idan Segev
- Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
- Department of Neurobiology, The Hebrew University of Jerusalem, Jerusalem, Israel
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46
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Wybo WAM, Torben-Nielsen B, Nevian T, Gewaltig MO. Electrical Compartmentalization in Neurons. Cell Rep 2020; 26:1759-1773.e7. [PMID: 30759388 DOI: 10.1016/j.celrep.2019.01.074] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2018] [Revised: 10/03/2018] [Accepted: 01/17/2019] [Indexed: 12/31/2022] Open
Abstract
The dendritic tree of neurons plays an important role in information processing in the brain. While it is thought that dendrites require independent subunits to perform most of their computations, it is still not understood how they compartmentalize into functional subunits. Here, we show how these subunits can be deduced from the properties of dendrites. We devised a formalism that links the dendritic arborization to an impedance-based tree graph and show how the topology of this graph reveals independent subunits. This analysis reveals that cooperativity between synapses decreases slowly with increasing electrical separation and thus that few independent subunits coexist. We nevertheless find that balanced inputs or shunting inhibition can modify this topology and increase the number and size of the subunits in a context-dependent manner. We also find that this dynamic recompartmentalization can enable branch-specific learning of stimulus features. Analysis of dendritic patch-clamp recording experiments confirmed our theoretical predictions.
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Affiliation(s)
- Willem A M Wybo
- Blue Brain Project, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland; Laboratory of Computational Neuroscience, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland; Department of Physiology, University of Bern, Bern, Switzerland
| | - Benjamin Torben-Nielsen
- Biocomputation Group, University of Hertfordshire, Hertfordshire, UK; Neurolinx Research Institute, La Jolla, CA, USA.
| | - Thomas Nevian
- Department of Physiology, University of Bern, Bern, Switzerland
| | - Marc-Oliver Gewaltig
- Blue Brain Project, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland
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47
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Ujfalussy BB, Makara JK. Impact of functional synapse clusters on neuronal response selectivity. Nat Commun 2020; 11:1413. [PMID: 32179739 PMCID: PMC7075899 DOI: 10.1038/s41467-020-15147-6] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2019] [Accepted: 02/20/2020] [Indexed: 12/24/2022] Open
Abstract
Clustering of functionally similar synapses in dendrites is thought to affect neuronal input-output transformation by triggering local nonlinearities. However, neither the in vivo impact of synaptic clusters on somatic membrane potential (sVm), nor the rules of cluster formation are elucidated. We develop a computational approach to measure the effect of functional synaptic clusters on sVm response of biophysical model CA1 and L2/3 pyramidal neurons to in vivo-like inputs. We demonstrate that small synaptic clusters appearing with random connectivity do not influence sVm. With structured connectivity, ~10-20 synapses/cluster are optimal for clustering-based tuning via state-dependent mechanisms, but larger selectivity is achieved by 2-fold potentiation of the same synapses. We further show that without nonlinear amplification of the effect of random clusters, action potential-based, global plasticity rules cannot generate functional clustering. Our results suggest that clusters likely form via local synaptic interactions, and have to be moderately large to impact sVm responses.
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Affiliation(s)
- Balázs B Ujfalussy
- Laboratory of Neuronal Signaling, Institute of Experimental Medicine, 1083, Budapest, Hungary.
| | - Judit K Makara
- Laboratory of Neuronal Signaling, Institute of Experimental Medicine, 1083, Budapest, Hungary
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48
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Roome CJ, Kuhn B. Voltage imaging with ANNINE dyes and two-photon microscopy of Purkinje dendrites in awake mice. Neurosci Res 2020; 152:15-24. [DOI: 10.1016/j.neures.2019.11.007] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2019] [Revised: 11/07/2019] [Accepted: 11/12/2019] [Indexed: 12/13/2022]
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49
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Synaptic Plasticity Depends on the Fine-Scale Input Pattern in Thin Dendrites of CA1 Pyramidal Neurons. J Neurosci 2020; 40:2593-2605. [PMID: 32047054 PMCID: PMC7096145 DOI: 10.1523/jneurosci.2071-19.2020] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2019] [Revised: 01/16/2020] [Accepted: 01/23/2020] [Indexed: 12/19/2022] Open
Abstract
Coordinated long-term plasticity of nearby excitatory synaptic inputs has been proposed to shape experience-related neuronal information processing. To elucidate the induction rules leading to spatially structured forms of synaptic potentiation in dendrites, we explored plasticity of glutamate uncaging-evoked excitatory input patterns with various spatial distributions in perisomatic dendrites of CA1 pyramidal neurons in slices from adult male rats. Coordinated long-term plasticity of nearby excitatory synaptic inputs has been proposed to shape experience-related neuronal information processing. To elucidate the induction rules leading to spatially structured forms of synaptic potentiation in dendrites, we explored plasticity of glutamate uncaging-evoked excitatory input patterns with various spatial distributions in perisomatic dendrites of CA1 pyramidal neurons in slices from adult male rats. We show that (1) the cooperativity rules governing the induction of synaptic LTP depend on dendritic location; (2) LTP of input patterns that are subthreshold or suprathreshold to evoke local dendritic spikes (d-spikes) requires different spatial organization; and (3) input patterns evoking d-spikes can strengthen nearby, nonsynchronous synapses by local heterosynaptic plasticity crosstalk mediated by NMDAR-dependent MEK/ERK signaling. These results suggest that multiple mechanisms can trigger spatially organized synaptic plasticity on various spatial and temporal scales, enriching the ability of neurons to use synaptic clustering for information processing. SIGNIFICANCE STATEMENT A fundamental question in neuroscience is how neuronal feature selectivity is established via the combination of dendritic processing of synaptic input patterns with long-term synaptic plasticity. As these processes have been mostly studied separately, the relationship between the rules of integration and rules of plasticity remained elusive. Here we explore how the fine-grained spatial pattern and the form of voltage integration determine plasticity of different excitatory synaptic input patterns in perisomatic dendrites of CA1 pyramidal cells. We demonstrate that the plasticity rules depend highly on three factors: (1) the location of the input within the dendritic branch (proximal vs distal), (2) the strength of the input pattern (subthreshold or suprathreshold for dendritic spikes), and (3) the stimulation of neighboring synapses.
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50
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Niculescu D, Michaelsen-Preusse K, Güner Ü, van Dorland R, Wierenga CJ, Lohmann C. A BDNF-Mediated Push-Pull Plasticity Mechanism for Synaptic Clustering. Cell Rep 2020; 24:2063-2074. [PMID: 30134168 DOI: 10.1016/j.celrep.2018.07.073] [Citation(s) in RCA: 51] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2017] [Revised: 06/12/2018] [Accepted: 07/23/2018] [Indexed: 01/09/2023] Open
Abstract
During development, activity-dependent synaptic plasticity refines neuronal networks with high precision. For example, spontaneous activity helps sorting synaptic inputs with similar activity patterns into clusters to enhance neuronal computations in the mature brain. Here, we show that TrkB activation and postsynaptic brain-derived neurotrophic factor (BDNF) are required for synaptic clustering in developing hippocampal neurons. Moreover, BDNF and TrkB modulate transmission at synapses depending on their clustering state, indicating that endogenous BDNF/TrkB signaling stabilizes locally synchronized synapses. Together with our previous data on proBDNF/p75NTR signaling, these findings suggest a push-pull plasticity mechanism for synaptic clustering: BDNF stabilizes clustered synapses while proBDNF downregulates out-of-sync synapses. This idea is supported by our observation that synaptic clustering requires matrix-metalloproteinase-9 activity, a proBDNF-to-BDNF converting enzyme. Finally, NMDA receptor activation mediates out-of-sync depression upstream of proBDNF signaling. Together, these data delineate an efficient plasticity mechanism where proBDNF and mature BDNF establish synaptic clustering through antagonistic modulation of synaptic transmission.
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Affiliation(s)
- Dragos Niculescu
- Department of Synapse and Network Development, Netherlands Institute for Neuroscience, 1105 Amsterdam, the Netherlands; Department of Neurogenesis and Circuit Development, Vision Institute, 75012 Paris, France
| | - Kristin Michaelsen-Preusse
- Department of Synapse and Network Development, Netherlands Institute for Neuroscience, 1105 Amsterdam, the Netherlands
| | - Ülkü Güner
- Department of Synapse and Network Development, Netherlands Institute for Neuroscience, 1105 Amsterdam, the Netherlands
| | - René van Dorland
- Department of Biology, Faculty of Science, Utrecht University, 3584 Utrecht, the Netherlands
| | - Corette J Wierenga
- Department of Biology, Faculty of Science, Utrecht University, 3584 Utrecht, the Netherlands
| | - Christian Lohmann
- Department of Synapse and Network Development, Netherlands Institute for Neuroscience, 1105 Amsterdam, the Netherlands; Department of Functional Genomics, Center for Neurogenomics and Cognitive Research, VU University, Amsterdam, the Netherlands.
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