1
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Rupprecht P, Duss SN, Becker D, Lewis CM, Bohacek J, Helmchen F. Centripetal integration of past events in hippocampal astrocytes regulated by locus coeruleus. Nat Neurosci 2024; 27:927-939. [PMID: 38570661 PMCID: PMC11089000 DOI: 10.1038/s41593-024-01612-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Accepted: 02/26/2024] [Indexed: 04/05/2024]
Abstract
An essential feature of neurons is their ability to centrally integrate information from their dendrites. The activity of astrocytes, in contrast, has been described as mostly uncoordinated across cellular compartments without clear central integration. Here we report conditional integration of calcium signals in astrocytic distal processes at their soma. In the hippocampus of adult mice of both sexes, we found that global astrocytic activity, as recorded with population calcium imaging, reflected past neuronal and behavioral events on a timescale of seconds. Salient past events, indicated by pupil dilations, facilitated the propagation of calcium signals from distal processes to the soma. Centripetal propagation to the soma was reproduced by optogenetic activation of the locus coeruleus, a key regulator of arousal, and reduced by pharmacological inhibition of α1-adrenergic receptors. Together, our results suggest that astrocytes are computational units of the brain that slowly and conditionally integrate calcium signals upon behaviorally relevant events.
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Affiliation(s)
- Peter Rupprecht
- Laboratory of Neural Circuit Dynamics, Brain Research Institute, University of Zurich, Zürich, Switzerland.
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zürich, Switzerland.
| | - Sian N Duss
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zürich, Switzerland
- Laboratory of Molecular and Behavioral Neuroscience, Institute for Neuroscience, Department of Health Sciences and Technology, ETH Zurich, Zürich, Switzerland
| | - Denise Becker
- Laboratory of Neural Circuit Dynamics, Brain Research Institute, University of Zurich, Zürich, Switzerland
| | - Christopher M Lewis
- Laboratory of Neural Circuit Dynamics, Brain Research Institute, University of Zurich, Zürich, Switzerland
| | - Johannes Bohacek
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zürich, Switzerland
- Laboratory of Molecular and Behavioral Neuroscience, Institute for Neuroscience, Department of Health Sciences and Technology, ETH Zurich, Zürich, Switzerland
| | - Fritjof Helmchen
- Laboratory of Neural Circuit Dynamics, Brain Research Institute, University of Zurich, Zürich, Switzerland.
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zürich, Switzerland.
- University Research Priority Program (URPP), Adaptive Brain Circuits in Development and Learning, University of Zurich, Zürich, Switzerland.
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2
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Lagzi F, Fairhall AL. Emergence of co-tuning in inhibitory neurons as a network phenomenon mediated by randomness, correlations, and homeostatic plasticity. SCIENCE ADVANCES 2024; 10:eadi4350. [PMID: 38507489 DOI: 10.1126/sciadv.adi4350] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Accepted: 02/15/2024] [Indexed: 03/22/2024]
Abstract
Cortical excitatory neurons show clear tuning to stimulus features, but the tuning properties of inhibitory interneurons are ambiguous. While inhibitory neurons have been considered to be largely untuned, some studies show that some parvalbumin-expressing (PV) neurons do show feature selectivity and participate in co-tuned subnetworks with pyramidal neurons. In this study, we first use mean-field theory to demonstrate that a combination of homeostatic plasticity governing the synaptic dynamics of the connections from PV to excitatory neurons, heterogeneity in the excitatory postsynaptic potentials that impinge on PV neurons, and shared correlated input from layer 4 results in the functional and structural self-organization of PV subnetworks. Second, we show that structural and functional feature tuning of PV neurons emerges more clearly at the network level, i.e., that population-level measures identify functional and structural co-tuning of PV neurons that are not evident in pairwise individual-level measures. Finally, we show that such co-tuning can enhance network stability at the cost of reduced feature selectivity.
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Affiliation(s)
- Fereshteh Lagzi
- Department of Physiology and Biophysics, University of Washington, 1705 NE Pacific Street, Seattle, WA 98195-7290, USA
- Computational Neuroscience Center, University of Washington, 1705 NE Pacific Street, Seattle, WA 98195-7290, USA
| | - Adrienne L Fairhall
- Department of Physiology and Biophysics, University of Washington, 1705 NE Pacific Street, Seattle, WA 98195-7290, USA
- Computational Neuroscience Center, University of Washington, 1705 NE Pacific Street, Seattle, WA 98195-7290, USA
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3
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Liang J, Yang Z, Zhou C. Excitation-Inhibition Balance, Neural Criticality, and Activities in Neuronal Circuits. Neuroscientist 2024:10738584231221766. [PMID: 38291889 DOI: 10.1177/10738584231221766] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
Neural activities in local circuits exhibit complex and multilevel dynamic features. Individual neurons spike irregularly, which is believed to originate from receiving balanced amounts of excitatory and inhibitory inputs, known as the excitation-inhibition balance. The spatial-temporal cascades of clustered neuronal spikes occur in variable sizes and durations, manifested as neural avalanches with scale-free features. These may be explained by the neural criticality hypothesis, which posits that neural systems operate around the transition between distinct dynamic states. Here, we summarize the experimental evidence for and the underlying theory of excitation-inhibition balance and neural criticality. Furthermore, we review recent studies of excitatory-inhibitory networks with synaptic kinetics as a simple solution to reconcile these two apparently distinct theories in a single circuit model. This provides a more unified understanding of multilevel neural activities in local circuits, from spontaneous to stimulus-response dynamics.
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Affiliation(s)
- Junhao Liang
- Eberhard Karls University of Tübingen and Max Planck Institute for Biological Cybernetics, Tübingen, Germany
| | - Zhuda Yang
- Department of Physics, Centre for Nonlinear Studies and Beijing-Hong Kong-Singapore Joint Centre for Nonlinear and Complex Systems (Hong Kong), Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Kowloon Tong, Hong Kong
| | - Changsong Zhou
- Department of Physics, Centre for Nonlinear Studies and Beijing-Hong Kong-Singapore Joint Centre for Nonlinear and Complex Systems (Hong Kong), Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Kowloon Tong, Hong Kong
- Life Science Imaging Centre, Hong Kong Baptist University, Kowloon Tong, Hong Kong
- Research Centre, Hong Kong Baptist University Institute of Research and Continuing Education, Shenzhen, China
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4
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Anneser L, Satou C, Hotz HR, Friedrich RW. Molecular organization of neuronal cell types and neuromodulatory systems in the zebrafish telencephalon. Curr Biol 2024; 34:298-312.e4. [PMID: 38157860 PMCID: PMC10808507 DOI: 10.1016/j.cub.2023.12.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 11/30/2023] [Accepted: 12/04/2023] [Indexed: 01/03/2024]
Abstract
The function of neuronal networks is determined not only by synaptic connectivity but also by neuromodulatory systems that broadcast information via distributed connections and volume transmission. To understand the molecular constraints that organize neuromodulatory signaling in the telencephalon of adult zebrafish, we used transcriptomics and additional approaches to delineate cell types, to determine their phylogenetic conservation, and to map the expression of marker genes at high granularity. The combinatorial expression of GPCRs and cell-type markers indicates that all neuronal cell types are subject to modulation by multiple monoaminergic systems and distinct combinations of neuropeptides. Individual cell types were associated with multiple (typically >30) neuromodulatory signaling networks but expressed only a few diagnostic GPCRs at high levels, suggesting that different neuromodulatory systems act in combination, albeit with unequal weights. These results provide a detailed map of cell types and brain areas in the zebrafish telencephalon, identify core components of neuromodulatory networks, highlight the cell-type specificity of neuropeptides and GPCRs, and begin to decipher the logic of combinatorial neuromodulation.
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Affiliation(s)
- Lukas Anneser
- Friedrich Miescher Institute for Biomedical Research, Maulbeerstrasse 66, 4058 Basel, Switzerland
| | - Chie Satou
- Friedrich Miescher Institute for Biomedical Research, Maulbeerstrasse 66, 4058 Basel, Switzerland
| | - Hans-Rudolf Hotz
- Friedrich Miescher Institute for Biomedical Research, Maulbeerstrasse 66, 4058 Basel, Switzerland
| | - Rainer W Friedrich
- Friedrich Miescher Institute for Biomedical Research, Maulbeerstrasse 66, 4058 Basel, Switzerland; University of Basel, 4003 Basel, Switzerland.
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5
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Ekelmans P, Kraynyukovas N, Tchumatchenko T. Targeting operational regimes of interest in recurrent neural networks. PLoS Comput Biol 2023; 19:e1011097. [PMID: 37186668 DOI: 10.1371/journal.pcbi.1011097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 05/25/2023] [Accepted: 04/11/2023] [Indexed: 05/17/2023] Open
Abstract
Neural computations emerge from local recurrent neural circuits or computational units such as cortical columns that comprise hundreds to a few thousand neurons. Continuous progress in connectomics, electrophysiology, and calcium imaging require tractable spiking network models that can consistently incorporate new information about the network structure and reproduce the recorded neural activity features. However, for spiking networks, it is challenging to predict which connectivity configurations and neural properties can generate fundamental operational states and specific experimentally reported nonlinear cortical computations. Theoretical descriptions for the computational state of cortical spiking circuits are diverse, including the balanced state where excitatory and inhibitory inputs balance almost perfectly or the inhibition stabilized state (ISN) where the excitatory part of the circuit is unstable. It remains an open question whether these states can co-exist with experimentally reported nonlinear computations and whether they can be recovered in biologically realistic implementations of spiking networks. Here, we show how to identify spiking network connectivity patterns underlying diverse nonlinear computations such as XOR, bistability, inhibitory stabilization, supersaturation, and persistent activity. We establish a mapping between the stabilized supralinear network (SSN) and spiking activity which allows us to pinpoint the location in parameter space where these activity regimes occur. Notably, we find that biologically-sized spiking networks can have irregular asynchronous activity that does not require strong excitation-inhibition balance or large feedforward input and we show that the dynamic firing rate trajectories in spiking networks can be precisely targeted without error-driven training algorithms.
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Affiliation(s)
- Pierre Ekelmans
- Theory of Neural Dynamics group, Max Planck Institute for Brain Research, Frankfurt am Main, Germany
- Frankfurt Institute for Advanced Studies, Frankfurt am Main, Germany
| | - Nataliya Kraynyukovas
- Theory of Neural Dynamics group, Max Planck Institute for Brain Research, Frankfurt am Main, Germany
- Institute of Experimental Epileptology and Cognition Research, Life and Brain Center, Universitätsklinikum Bonn, Bonn, Germany
| | - Tatjana Tchumatchenko
- Theory of Neural Dynamics group, Max Planck Institute for Brain Research, Frankfurt am Main, Germany
- Institute of Experimental Epileptology and Cognition Research, Life and Brain Center, Universitätsklinikum Bonn, Bonn, Germany
- Institute of physiological chemistry, Medical center of the Johannes Gutenberg-University Mainz, Mainz, Germany
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6
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Hageter J, Starkey J, Horstick EJ. Thalamic regulation of a visual critical period and motor behavior. Cell Rep 2023; 42:112287. [PMID: 36952349 PMCID: PMC10514242 DOI: 10.1016/j.celrep.2023.112287] [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: 10/14/2022] [Revised: 02/02/2023] [Accepted: 03/03/2023] [Indexed: 03/24/2023] Open
Abstract
During the visual critical period (CP), sensory experience refines the structure and function of visual circuits. The basis of this plasticity was long thought to be limited to cortical circuits, but recently described thalamic plasticity challenges this dogma and demonstrates greater complexity underlying visual plasticity. Yet how visual experience modulates thalamic neurons or how the thalamus modulates CP timing is incompletely understood. Using a larval zebrafish, thalamus-centric ocular dominance model, we show functional changes in the thalamus and a role of inhibitory signaling to establish CP timing using a combination of functional imaging, optogenetics, and pharmacology. Hemisphere-specific changes in genetically defined thalamic neurons correlate with changes in visuomotor behavior, establishing a role of thalamic plasticity in modulating motor performance. Our work demonstrates that visual plasticity is broadly conserved and that visual experience leads to neuron-level functional changes in the thalamus that require inhibitory signaling to establish critical period timing.
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Affiliation(s)
- John Hageter
- Department of Biology, West Virginia University, Morgantown, WV 26506, USA
| | - Jacob Starkey
- Department of Biology, West Virginia University, Morgantown, WV 26506, USA
| | - Eric J Horstick
- Department of Biology, West Virginia University, Morgantown, WV 26506, USA; Department of Neuroscience, West Virginia University, Morgantown, WV 26506, USA.
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7
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Wu YK, Miehl C, Gjorgjieva J. Regulation of circuit organization and function through inhibitory synaptic plasticity. Trends Neurosci 2022; 45:884-898. [PMID: 36404455 DOI: 10.1016/j.tins.2022.10.006] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Revised: 10/02/2022] [Accepted: 10/04/2022] [Indexed: 11/15/2022]
Abstract
Diverse inhibitory neurons in the mammalian brain shape circuit connectivity and dynamics through mechanisms of synaptic plasticity. Inhibitory plasticity can establish excitation/inhibition (E/I) balance, control neuronal firing, and affect local calcium concentration, hence regulating neuronal activity at the network, single neuron, and dendritic level. Computational models can synthesize multiple experimental results and provide insight into how inhibitory plasticity controls circuit dynamics and sculpts connectivity by identifying phenomenological learning rules amenable to mathematical analysis. We highlight recent studies on the role of inhibitory plasticity in modulating excitatory plasticity, forming structured networks underlying memory formation and recall, and implementing adaptive phenomena and novelty detection. We conclude with experimental and modeling progress on the role of interneuron-specific plasticity in circuit computation and context-dependent learning.
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Affiliation(s)
- Yue Kris Wu
- School of Life Sciences, Technical University of Munich, Freising, Germany; Max Planck Institute for Brain Research, Frankfurt, Germany
| | - Christoph Miehl
- School of Life Sciences, Technical University of Munich, Freising, Germany; Max Planck Institute for Brain Research, Frankfurt, Germany
| | - Julijana Gjorgjieva
- School of Life Sciences, Technical University of Munich, Freising, Germany; Max Planck Institute for Brain Research, Frankfurt, Germany.
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8
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Satou C, Neve RL, Oyibo HK, Zmarz P, Huang KH, Arn Bouldoires E, Mori T, Higashijima SI, Keller GB, Friedrich RW. A viral toolbox for conditional and transneuronal gene expression in zebrafish. eLife 2022; 11:77153. [PMID: 35866706 PMCID: PMC9307271 DOI: 10.7554/elife.77153] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Accepted: 07/06/2022] [Indexed: 12/13/2022] Open
Abstract
The zebrafish is an important model in systems neuroscience but viral tools to dissect the structure and function of neuronal circuitry are not established. We developed methods for efficient gene transfer and retrograde tracing in adult and larval zebrafish by herpes simplex viruses (HSV1). HSV1 was combined with the Gal4/UAS system to target cell types with high spatial, temporal, and molecular specificity. We also established methods for efficient transneuronal tracing by modified rabies viruses in zebrafish. We demonstrate that HSV1 and rabies viruses can be used to visualize and manipulate genetically or anatomically identified neurons within and across different brain areas of adult and larval zebrafish. An expandable library of viruses is provided to express fluorescent proteins, calcium indicators, optogenetic probes, toxins and other molecular tools. This toolbox creates new opportunities to interrogate neuronal circuits in zebrafish through combinations of genetic and viral approaches.
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Affiliation(s)
- Chie Satou
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland
| | - Rachael L Neve
- Gene Delivery Technology Core, Massachusetts General Hospital, Cambridge, United States
| | - Hassana K Oyibo
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland
| | - Pawel Zmarz
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland
| | - Kuo-Hua Huang
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland
| | | | - Takuma Mori
- Department of Molecular and Cellular Physiology, Institute of Medicine, Academic Assembly, Shinshu University, Nagano, Japan
| | - Shin-Ichi Higashijima
- National Institutes of Natural Sciences, Exploratory Research Center on Life and Living Systems, National Institute for Basic Biology, Okazaki, Japan.,Graduate University for Advanced Studies, Okazaki, Japan
| | - Georg B Keller
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland.,Faculty of Natural Sciences, University of Basel, Basel, Switzerland
| | - Rainer W Friedrich
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland.,Faculty of Natural Sciences, University of Basel, Basel, Switzerland
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9
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Keijser J, Sprekeler H. Optimizing interneuron circuits for compartment-specific feedback inhibition. PLoS Comput Biol 2022; 18:e1009933. [PMID: 35482670 PMCID: PMC9049365 DOI: 10.1371/journal.pcbi.1009933] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Accepted: 02/18/2022] [Indexed: 12/02/2022] Open
Abstract
Cortical circuits process information by rich recurrent interactions between excitatory neurons and inhibitory interneurons. One of the prime functions of interneurons is to stabilize the circuit by feedback inhibition, but the level of specificity on which inhibitory feedback operates is not fully resolved. We hypothesized that inhibitory circuits could enable separate feedback control loops for different synaptic input streams, by means of specific feedback inhibition to different neuronal compartments. To investigate this hypothesis, we adopted an optimization approach. Leveraging recent advances in training spiking network models, we optimized the connectivity and short-term plasticity of interneuron circuits for compartment-specific feedback inhibition onto pyramidal neurons. Over the course of the optimization, the interneurons diversified into two classes that resembled parvalbumin (PV) and somatostatin (SST) expressing interneurons. Using simulations and mathematical analyses, we show that the resulting circuit can be understood as a neural decoder that inverts the nonlinear biophysical computations performed within the pyramidal cells. Our model provides a proof of concept for studying structure-function relations in cortical circuits by a combination of gradient-based optimization and biologically plausible phenomenological models. The brain contains billions of nerve cells—neurons—that can be classified into different types depending on their shape, connectivity and activity. A particularly diverse group of neurons is that of inhibitory neurons, named after their suppressive effect on neural activity. Presumably, their diverse properties allow inhibitory neurons to fulfil different functions, but what these functions are is currently unclear. In this paper, we investigated if a particular function can explain the existence and properties of the two most common inhibitory cell classes: The need to regulate activity in different physical parts (compartments) of the neurons they target. We investigated this function in a computer model, using optimization to find the neuron properties best-suited for compartment-specific inhibition. Our key result is that after the optimization, model neurons largely fell into two classes that resembled the two types of biological neurons. In particular, the optimized neurons were connected to only one compartment of other neurons. This suggests that the diversity of inhibitory neurons is well suited for compartment-specific inhibition. In the future, our approach of optimizing neural properties might be used to investigate other functions (or dysfunctions) of neuron diversity.
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Affiliation(s)
- Joram Keijser
- Modelling of Cognitive Processes, Institute of Software Engineering and Theoretical Computer Science, Technische Universität Berlin, Berlin, Germany
- Charité – Universitätsmedizin Berlin, Einstein Center for Neurosciences Berlin, Berlin, Germany
- * E-mail:
| | - Henning Sprekeler
- Modelling of Cognitive Processes, Institute of Software Engineering and Theoretical Computer Science, Technische Universität Berlin, Berlin, Germany
- Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany
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10
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Wu YK, Zenke F. Nonlinear transient amplification in recurrent neural networks with short-term plasticity. eLife 2021; 10:71263. [PMID: 34895468 PMCID: PMC8820736 DOI: 10.7554/elife.71263] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Accepted: 12/10/2021] [Indexed: 11/24/2022] Open
Abstract
To rapidly process information, neural circuits have to amplify specific activity patterns transiently. How the brain performs this nonlinear operation remains elusive. Hebbian assemblies are one possibility whereby strong recurrent excitatory connections boost neuronal activity. However, such Hebbian amplification is often associated with dynamical slowing of network dynamics, non-transient attractor states, and pathological run-away activity. Feedback inhibition can alleviate these effects but typically linearizes responses and reduces amplification gain. Here, we study nonlinear transient amplification (NTA), a plausible alternative mechanism that reconciles strong recurrent excitation with rapid amplification while avoiding the above issues. NTA has two distinct temporal phases. Initially, positive feedback excitation selectively amplifies inputs that exceed a critical threshold. Subsequently, short-term plasticity quenches the run-away dynamics into an inhibition-stabilized network state. By characterizing NTA in supralinear network models, we establish that the resulting onset transients are stimulus selective and well-suited for speedy information processing. Further, we find that excitatory-inhibitory co-tuning widens the parameter regime in which NTA is possible in the absence of persistent activity. In summary, NTA provides a parsimonious explanation for how excitatory-inhibitory co-tuning and short-term plasticity collaborate in recurrent networks to achieve transient amplification.
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Affiliation(s)
- Yue Kris Wu
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland
| | - Friedemann Zenke
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland
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11
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Rupprecht P, Carta S, Hoffmann A, Echizen M, Blot A, Kwan AC, Dan Y, Hofer SB, Kitamura K, Helmchen F, Friedrich RW. A database and deep learning toolbox for noise-optimized, generalized spike inference from calcium imaging. Nat Neurosci 2021; 24:1324-1337. [PMID: 34341584 PMCID: PMC7611618 DOI: 10.1038/s41593-021-00895-5] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Accepted: 06/23/2021] [Indexed: 02/06/2023]
Abstract
Inference of action potentials ('spikes') from neuronal calcium signals is complicated by the scarcity of simultaneous measurements of action potentials and calcium signals ('ground truth'). In this study, we compiled a large, diverse ground truth database from publicly available and newly performed recordings in zebrafish and mice covering a broad range of calcium indicators, cell types and signal-to-noise ratios, comprising a total of more than 35 recording hours from 298 neurons. We developed an algorithm for spike inference (termed CASCADE) that is based on supervised deep networks, takes advantage of the ground truth database, infers absolute spike rates and outperforms existing model-based algorithms. To optimize performance for unseen imaging data, CASCADE retrains itself by resampling ground truth data to match the respective sampling rate and noise level; therefore, no parameters need to be adjusted by the user. In addition, we developed systematic performance assessments for unseen data, openly released a resource toolbox and provide a user-friendly cloud-based implementation.
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Affiliation(s)
- Peter Rupprecht
- Brain Research Institute, University of Zürich, Zurich, Switzerland.
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland.
| | - Stefano Carta
- Brain Research Institute, University of Zürich, Zurich, Switzerland
| | - Adrian Hoffmann
- Brain Research Institute, University of Zürich, Zurich, Switzerland
| | - Mayumi Echizen
- Department of Neurophysiology, University of Tokyo, Tokyo, Japan
- Department of Anesthesiology, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan
| | - Antonin Blot
- Sainsbury Wellcome Centre for Neural Circuits and Behaviour, University College London, London, United Kingdom
- Biozentrum, University of Basel, Basel, Switzerland
| | - Alex C Kwan
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Yang Dan
- Division of Neurobiology, Department of Molecular and Cell Biology, Helen Wills Neuroscience Institute, Howard Hughes Medical Institute, University of California, Berkeley, Berkeley CA, USA
| | - Sonja B Hofer
- Sainsbury Wellcome Centre for Neural Circuits and Behaviour, University College London, London, United Kingdom
- Biozentrum, University of Basel, Basel, Switzerland
| | - Kazuo Kitamura
- Department of Neurophysiology, University of Tokyo, Tokyo, Japan
- Department of Neurophysiology, University of Yamanashi, Yamanashi, Japan
| | - Fritjof Helmchen
- Brain Research Institute, University of Zürich, Zurich, Switzerland.
| | - Rainer W Friedrich
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland.
- University of Basel, Basel, Switzerland.
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12
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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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13
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Friedrich RW, Wanner AA. Dense Circuit Reconstruction to Understand Neuronal Computation: Focus on Zebrafish. Annu Rev Neurosci 2021; 44:275-293. [PMID: 33730512 DOI: 10.1146/annurev-neuro-110220-013050] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The dense reconstruction of neuronal wiring diagrams from volumetric electron microscopy data has the potential to generate fundamentally new insights into mechanisms of information processing and storage in neuronal circuits. Zebrafish provide unique opportunities for dynamical connectomics approaches that combine reconstructions of wiring diagrams with measurements of neuronal population activity and behavior. Such approaches have the power to reveal higher-order structure in wiring diagrams that cannot be detected by sparse sampling of connectivity and that is essential for neuronal computations. In the brain stem, recurrently connected neuronal modules were identified that can account for slow, low-dimensional dynamics in an integrator circuit. In the spinal cord, connectivity specifies functional differences between premotor interneurons. In the olfactory bulb, tuning-dependent connectivity implements a whitening transformation that is based on the selective suppression of responses to overrepresented stimulus features. These findings illustrate the potential of dynamical connectomics in zebrafish to analyze the circuit mechanisms underlying higher-order neuronal computations.
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Affiliation(s)
- Rainer W Friedrich
- Friedrich Miescher Institute for Biomedical Research, 4058 Basel, Switzerland; .,Faculty of Natural Sciences, University of Basel, 4003 Basel, Switzerland
| | - Adrian A Wanner
- Princeton Neuroscience Institute, Princeton University, Princeton, New Jersey 08544, USA;
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14
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Jain V, Murphy-Baum BL, deRosenroll G, Sethuramanujam S, Delsey M, Delaney KR, Awatramani GB. The functional organization of excitation and inhibition in the dendrites of mouse direction-selective ganglion cells. eLife 2020; 9:52949. [PMID: 32096758 PMCID: PMC7069718 DOI: 10.7554/elife.52949] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Accepted: 02/24/2020] [Indexed: 12/14/2022] Open
Abstract
Recent studies indicate that the precise timing and location of excitation and inhibition (E/I) within active dendritic trees can significantly impact neuronal function. How synaptic inputs are functionally organized at the subcellular level in intact circuits remains unclear. To address this issue, we took advantage of the retinal direction-selective ganglion cell circuit, where directionally tuned inhibition is known to shape non-directional excitatory signals. We combined two-photon calcium imaging with genetic, pharmacological, and single-cell ablation methods to examine the extent to which inhibition ‘vetoes’ excitation at the level of individual dendrites of direction-selective ganglion cells. We demonstrate that inhibition shapes direction selectivity independently within small dendritic segments (<10µm) with remarkable accuracy. The data suggest that the parallel processing schemes proposed for direction encoding could be more fine-grained than previously envisioned.
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Affiliation(s)
- Varsha Jain
- Department of Biology, University of Victoria, Victoria, Canada
| | | | | | | | - Mike Delsey
- Department of Biology, University of Victoria, Victoria, Canada
| | - Kerry R Delaney
- Department of Biology, University of Victoria, Victoria, Canada
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15
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Frank T, Mönig NR, Satou C, Higashijima SI, Friedrich RW. Associative conditioning remaps odor representations and modifies inhibition in a higher olfactory brain area. Nat Neurosci 2019; 22:1844-1856. [PMID: 31591559 PMCID: PMC6858881 DOI: 10.1038/s41593-019-0495-z] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2018] [Accepted: 08/09/2019] [Indexed: 11/30/2022]
Abstract
Intelligent behavior involves associations between high-dimensional sensory representations and behaviorally relevant qualities such as valence. Learning of associations involves plasticity of excitatory connectivity but it remains poorly understood how information flow is reorganized in networks and how inhibition contributes to this process. We trained adult zebrafish in an appetitive odor discrimination task and analyzed odor representations in a specific compartment of telencephalic area Dp, the homolog of olfactory cortex. Associative conditioning enhanced responses with a preference for the positively conditioned odor (CS+). Moreover, conditioning systematically remapped odor representations along an axis in coding space that represented attractiveness (valence). Inter-individual variations in this mapping predicted variations in behavioral odor preference. Photoinhibition of interneurons resulted in specific modifications of odor representations that mirrored effects of conditioning and reduced experience-dependent, inter-individual variations in odor-valence mapping. These results reveal an individualized odor-to-valence map that is shaped by inhibition and reorganized during learning.
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Affiliation(s)
- Thomas Frank
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland.
| | - Nila R Mönig
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland.,University of Basel, Basel, Switzerland
| | - Chie Satou
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland
| | - Shin-Ichi Higashijima
- National Institutes of Natural Sciences, Exploratory Research Center on Life and Living Systems, National Institute for Basic Biology, Okazaki, Japan
| | - Rainer W Friedrich
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland. .,University of Basel, Basel, Switzerland.
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16
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Hemberger M, Shein-Idelson M, Pammer L, Laurent G. Reliable Sequential Activation of Neural Assemblies by Single Pyramidal Cells in a Three-Layered Cortex. Neuron 2019; 104:353-369.e5. [PMID: 31439429 DOI: 10.1016/j.neuron.2019.07.017] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2018] [Revised: 05/10/2019] [Accepted: 07/12/2019] [Indexed: 10/26/2022]
Abstract
Recent studies reveal the occasional impact of single neurons on surround firing statistics and even simple behaviors. Exploiting the advantages of a simple cortex, we examined the influence of single pyramidal neurons on surrounding cortical circuits. Brief activation of single neurons triggered reliable sequences of firing in tens of other excitatory and inhibitory cortical neurons, reflecting cascading activity through local networks, as indicated by delayed yet precisely timed polysynaptic subthreshold potentials. The evoked patterns were specific to the pyramidal cell of origin, extended over hundreds of micrometers from their source, and unfolded over up to 200 ms. Simultaneous activation of pyramidal cell pairs indicated balanced control of population activity, preventing paroxysmal amplification. Single cortical pyramidal neurons can thus trigger reliable postsynaptic activity that can propagate in a reliable fashion through cortex, generating rapidly evolving and non-random firing sequences reminiscent of those observed in mammalian hippocampus during "replay" and in avian song circuits.
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Affiliation(s)
- Mike Hemberger
- Max Planck Institute for Brain Research, Frankfurt am Main, 60438 Germany
| | - Mark Shein-Idelson
- Max Planck Institute for Brain Research, Frankfurt am Main, 60438 Germany; Department of Neurobiology, George S. Wise Faculty of Life Sciences, Sagol School for Neuroscience, Tel-Aviv University, Tel Aviv, Israel
| | - Lorenz Pammer
- Max Planck Institute for Brain Research, Frankfurt am Main, 60438 Germany
| | - Gilles Laurent
- Max Planck Institute for Brain Research, Frankfurt am Main, 60438 Germany.
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