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van Oostrum M, Schuman EM. Understanding the molecular diversity of synapses. Nat Rev Neurosci 2025; 26:65-81. [PMID: 39638892 DOI: 10.1038/s41583-024-00888-w] [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: 11/08/2024] [Indexed: 12/07/2024]
Abstract
Synapses are composed of thousands of proteins, providing the potential for extensive molecular diversity to shape synapse type-specific functional specializations. In this Review, we explore the landscape of synaptic diversity and describe the mechanisms that expand the molecular complexity of synapses, from the genotype to the regulation of gene expression to the production of specific proteoforms and the formation of localized protein complexes. We emphasize the importance of examining every molecular layer and adopting a systems perspective to understand how these interconnected mechanisms shape the diverse functional and structural properties of synapses. We explore current frameworks for classifying synapses and methodologies for investigating different synapse types at varying scales, from synapse-type-specific proteomics to advanced imaging techniques with single-synapse resolution. We highlight the potential of synapse-type-specific approaches for integrating molecular data with cellular functions, circuit organization and organismal phenotypes to enable a more holistic exploration of neuronal phenomena across different scales.
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Affiliation(s)
- Marc van Oostrum
- Max Planck Institute for Brain Research, Frankfurt am Main, Germany
- Biozentrum, University of Basel, Basel, Switzerland
| | - Erin M Schuman
- Max Planck Institute for Brain Research, Frankfurt am Main, Germany.
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2
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Albantakis L, Bernard C, Brenner N, Marder E, Narayanan R. The Brain's Best Kept Secret Is Its Degenerate Structure. J Neurosci 2024; 44:e1339242024. [PMID: 39358027 PMCID: PMC11450540 DOI: 10.1523/jneurosci.1339-24.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2024] [Revised: 07/26/2024] [Accepted: 07/29/2024] [Indexed: 10/04/2024] Open
Abstract
Degeneracy is defined as multiple sets of solutions that can produce very similar system performance. Degeneracy is seen across phylogenetic scales, in all kinds of organisms. In neuroscience, degeneracy can be seen in the constellation of biophysical properties that produce a neuron's characteristic intrinsic properties and/or the constellation of mechanisms that determine circuit outputs or behavior. Here, we present examples of degeneracy at multiple levels of organization, from single-cell behavior, small circuits, large circuits, and, in cognition, drawing conclusions from work ranging from bacteria to human cognition. Degeneracy allows the individual-to-individual variability within a population that creates potential for evolution.
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Affiliation(s)
- Larissa Albantakis
- Department of Psychiatry, University of Wisconsin-Madison, Madison, Wisconsin 53719
| | | | - Naama Brenner
- Department of Chemical Engineering and Network Biology Research Lab, Technion Israel Institute of Technology, Haifa 32000, Israel
| | - Eve Marder
- Biology Department and Volen Center Brandeis University Waltham, Massachusetts 02454
| | - Rishikesh Narayanan
- Cellular Neurophysiology Laboratory, Molecular Biophysics Unit, Indian Institute of Science, Bangalore 560012, India
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3
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Fyon A, Franci A, Sacré P, Drion G. Dimensionality reduction of neuronal degeneracy reveals two interfering physiological mechanisms. PNAS NEXUS 2024; 3:pgae415. [PMID: 39359396 PMCID: PMC11443964 DOI: 10.1093/pnasnexus/pgae415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/20/2024] [Accepted: 09/07/2024] [Indexed: 10/04/2024]
Abstract
Neuronal systems maintain stable functions despite large variability in their physiological components. Ion channel expression, in particular, is highly variable in neurons exhibiting similar electrophysiological phenotypes, which raises questions regarding how specific ion channel subsets reliably shape intrinsic properties of neurons. Here, we use detailed conductance-based modeling to explore how stable neuronal function is achieved despite variability in channel composition among neurons. Using dimensionality reduction, we uncover two principal dimensions in the channel conductance space that capture most of the variance of the observed variability. These two dimensions correspond to two sources of variability that originate from distinct physiologically relevant mechanisms underlying the regulation of neuronal activity, providing quantitative insights into how channel composition is linked to the electrophysiological activity of neurons. These insights allow us to understand and design a model-independent, reliable neuromodulation rule for variable neuronal populations.
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Affiliation(s)
- Arthur Fyon
- Department of Electrical Engineering and Computer Science, University of Liège, Liège B-4000, Belgium
| | - Alessio Franci
- Department of Electrical Engineering and Computer Science, University of Liège, Liège B-4000, Belgium
- WEL-T Department, WEL Research Institute, Wavre B-1300, Belgium
| | - Pierre Sacré
- Department of Electrical Engineering and Computer Science, University of Liège, Liège B-4000, Belgium
| | - Guillaume Drion
- Department of Electrical Engineering and Computer Science, University of Liège, Liège B-4000, Belgium
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4
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Griffith EY, ElSayed M, Dura-Bernal S, Neymotin SA, Uhlrich DJ, Lytton WW, Zhu JJ. Mechanism of an Intrinsic Oscillation in Rat Geniculate Interneurons. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.06.597830. [PMID: 38895250 PMCID: PMC11185623 DOI: 10.1101/2024.06.06.597830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
Depolarizing current injections produced a rhythmic bursting of action potentials - a bursting oscillation - in a set of local interneurons in the lateral geniculate nucleus (LGN) of rats. The current dynamics underlying this firing pattern have not been determined, though this cell type constitutes an important cellular component of thalamocortical circuitry, and contributes to both pathologic and non-pathologic brain states. We thus investigated the source of the bursting oscillation using pharmacological manipulations in LGN slices in vitro and in silico. 1. Selective blockade of calcium channel subtypes revealed that high-threshold calcium currentsI L andI P contributed strongly to the oscillation. 2. Increased extracellular K+ concentration (decreased K+currents) eliminated the oscillation. 3. Selective blockade of K+ channel subtypes demonstrated that the calcium-sensitive potassium current (I A H P ) was of primary importance. A morphologically simplified, multicompartment model of the thalamic interneuron characterized the oscillation as follows: 1. The low-threshold calcium currentI T provided the strong initial burst characteristic of the oscillation. 2. Alternating fluxes through high-threshold calcium channels andI A H P then provided the continuing oscillation's burst and interburst periods respectively. This interplay betweenI L andI A H P contrasts with the current dynamics underlying oscillations in thalamocortical and reticularis neurons, which primarily involveI T andI H , orI T andI A H P respectively. These findings thus point to a novel electrophysiological mechanism for generating intrinsic oscillations in a major thalamic cell type. Because local interneurons can sculpt the behavior of thalamocortical circuits, these results suggest new targets for the manipulation of ascending thalamocortical network activity.
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Affiliation(s)
- Erica Y Griffith
- Department of Neural and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY
- Center for Biomedical Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY
| | - Mohamed ElSayed
- Department of Psychiatry, Geisel School of Medicine at Dartmouth, Hanover, NH
- Department of Biomedical Engineering, SUNY Downstate School of Graduate Studies, Brooklyn, NY
- Department of Psychiatry, New Hampshire Hospital, Concord, NH
| | - Salvador Dura-Bernal
- Center for Biomedical Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY
- Department of Physiology and Pharmacology, SUNY Downstate Health Sciences University, Brooklyn, NY
| | - Samuel A Neymotin
- Center for Biomedical Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY
- Department of Psychiatry, New York University School of Medicine, New York, NY
| | - Daniel J Uhlrich
- Department of Neuroscience, University of Wisconsin-Madison, Madison, WI, USA
| | - William W Lytton
- Department of Physiology and Pharmacology, SUNY Downstate Health Sciences University, Brooklyn, NY
- Department of Neurology, Kings County Hospital, Brooklyn, NY
| | - J Julius Zhu
- Department of Pharmacology, University of Virginia School of Medicine, Charlottesville, VA
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5
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Arnaudon A, Reva M, Zbili M, Markram H, Van Geit W, Kanari L. Controlling morpho-electrophysiological variability of neurons with detailed biophysical models. iScience 2023; 26:108222. [PMID: 37953946 PMCID: PMC10638024 DOI: 10.1016/j.isci.2023.108222] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 07/21/2023] [Accepted: 10/12/2023] [Indexed: 11/14/2023] Open
Abstract
Variability, which is known to be a universal feature among biological units such as neuronal cells, holds significant importance, as, for example, it enables a robust encoding of a high volume of information in neuronal circuits and prevents hypersynchronizations. While most computational studies on electrophysiological variability in neuronal circuits were done with single-compartment neuron models, we instead focus on the variability of detailed biophysical models of neuron multi-compartmental morphologies. We leverage a Markov chain Monte Carlo method to generate populations of electrical models reproducing the variability of experimental recordings while being compatible with a set of morphologies to faithfully represent specifi morpho-electrical type. We demonstrate our approach on layer 5 pyramidal cells and study the morpho-electrical variability and in particular, find that morphological variability alone is insufficient to reproduce electrical variability. Overall, this approach provides a strong statistical basis to create detailed models of neurons with controlled variability.
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Affiliation(s)
- Alexis Arnaudon
- Blue Brain Project, École Polytechnique Fédérale de Lausanne (EPFL), Campus Biotech, Geneva, Switzerland
| | - Maria Reva
- Blue Brain Project, École Polytechnique Fédérale de Lausanne (EPFL), Campus Biotech, Geneva, Switzerland
| | - Mickael Zbili
- Blue Brain Project, École Polytechnique Fédérale de Lausanne (EPFL), Campus Biotech, Geneva, Switzerland
| | - Henry Markram
- Blue Brain Project, École Polytechnique Fédérale de Lausanne (EPFL), Campus Biotech, Geneva, Switzerland
| | - Werner Van Geit
- Blue Brain Project, École Polytechnique Fédérale de Lausanne (EPFL), Campus Biotech, Geneva, Switzerland
| | - Lida Kanari
- Blue Brain Project, École Polytechnique Fédérale de Lausanne (EPFL), Campus Biotech, Geneva, Switzerland
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6
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Marder E. Individual Variability, Statistics, and the Resilience of Nervous Systems of Crabs and Humans to Temperature and Other Perturbations. eNeuro 2023; 10:ENEURO.0425-23.2023. [PMID: 37963654 PMCID: PMC10646886 DOI: 10.1523/eneuro.0425-23.2023] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2023] [Accepted: 10/23/2023] [Indexed: 11/16/2023] Open
Affiliation(s)
- Eve Marder
- Volen Center and Biology Department, Brandeis University, Waltham, MA 02454
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7
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Srikanth S, Narayanan R. Heterogeneous off-target impact of ion-channel deletion on intrinsic properties of hippocampal model neurons that self-regulate calcium. Front Cell Neurosci 2023; 17:1241450. [PMID: 37904732 PMCID: PMC10613471 DOI: 10.3389/fncel.2023.1241450] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Accepted: 09/20/2023] [Indexed: 11/01/2023] Open
Abstract
How do neurons that implement cell-autonomous self-regulation of calcium react to knockout of individual ion-channel conductances? To address this question, we used a heterogeneous population of 78 conductance-based models of hippocampal pyramidal neurons that maintained cell-autonomous calcium homeostasis while receiving theta-frequency inputs. At calcium steady-state, we individually deleted each of the 11 active ion-channel conductances from each model. We measured the acute impact of deleting each conductance (one at a time) by comparing intrinsic electrophysiological properties before and immediately after channel deletion. The acute impact of deleting individual conductances on physiological properties (including calcium homeostasis) was heterogeneous, depending on the property, the specific model, and the deleted channel. The underlying many-to-many mapping between ion channels and properties pointed to ion-channel degeneracy. Next, we allowed the other conductances (barring the deleted conductance) to evolve towards achieving calcium homeostasis during theta-frequency activity. When calcium homeostasis was perturbed by ion-channel deletion, post-knockout plasticity in other conductances ensured resilience of calcium homeostasis to ion-channel deletion. These results demonstrate degeneracy in calcium homeostasis, as calcium homeostasis in knockout models was implemented in the absence of a channel that was earlier involved in the homeostatic process. Importantly, in reacquiring homeostasis, ion-channel conductances and physiological properties underwent heterogenous plasticity (dependent on the model, the property, and the deleted channel), even introducing changes in properties that were not directly connected to the deleted channel. Together, post-knockout plasticity geared towards maintaining homeostasis introduced heterogenous off-target effects on several channels and properties, suggesting that extreme caution be exercised in interpreting experimental outcomes involving channel knockouts.
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Affiliation(s)
- Sunandha Srikanth
- Cellular Neurophysiology Laboratory, Molecular Biophysics Unit, Indian Institute of Science, Bangalore, India
- Undergraduate Program, Indian Institute of Science, Bangalore, India
| | - Rishikesh Narayanan
- Cellular Neurophysiology Laboratory, Molecular Biophysics Unit, Indian Institute of Science, Bangalore, India
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8
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Viteri JA, Schulz DJ. Motor neurons within a network use cell-type specific feedback mechanisms to constrain relationships among ion channel mRNAs. J Neurophysiol 2023; 130:569-584. [PMID: 37529838 PMCID: PMC11550874 DOI: 10.1152/jn.00098.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 07/27/2023] [Accepted: 07/29/2023] [Indexed: 08/03/2023] Open
Abstract
Recently, activity has been proposed as a primary feedback mechanism used by continuously bursting neurons to coordinate ion channel mRNA relationships that underlie stable output. However, some neuron types only have intermittent periods of activity and so may require alternative mechanisms that induce and constrain the appropriate ion channel profile in different states of activity. To address this, we used the pyloric dilator (PD; constitutively active) and the lateral gastric (LG; periodically active) neurons of the stomatogastric ganglion (STG) of the crustacean Cancer borealis. We experimentally stimulated descending inputs to the STG to cause release of neuromodulators known to elicit the active state of LG neurons and quantified the mRNA abundances and pairwise relationships of 11 voltage-gated ion channels in active and silent LG neurons. The same stimulus does not significantly alter PD activity. Activation of LG upregulated ion channel mRNAs and lead to a greater number of positively correlated pairwise channel mRNA relationships. Conversely, this stimulus did not induce major changes in ion channel mRNA abundances and relationships of PD cells, suggesting their ongoing activity is sufficient to maintain channel mRNA relationships even under changing modulatory conditions. In addition, we found that ion channel mRNA correlations induced by the active state of LG are influenced by a combination of activity- and neuromodulator-dependent feedback mechanisms. Interestingly, some of these same correlations are maintained by distinct mechanisms in PD, suggesting that these motor networks use distinct feedback mechanisms to coordinate the same mRNA relationships across neuron types.NEW & NOTEWORTHY Neurons use various feedback mechanisms to adjust and maintain their output. Here, we demonstrate that different neurons within the same network can use distinct signaling mechanisms to regulate the same ion channel mRNA relationships.
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Affiliation(s)
- Jose A Viteri
- Division of Biological Sciences, University of Missouri-Columbia, Columbia, Missouri, United States
| | - David J Schulz
- Division of Biological Sciences, University of Missouri-Columbia, Columbia, Missouri, United States
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9
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Koch NA, Sonnenberg L, Hedrich UBS, Lauxmann S, Benda J. Loss or gain of function? Effects of ion channel mutations on neuronal firing depend on the neuron type. Front Neurol 2023; 14:1194811. [PMID: 37292138 PMCID: PMC10244640 DOI: 10.3389/fneur.2023.1194811] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 05/03/2023] [Indexed: 06/10/2023] Open
Abstract
Introduction Clinically relevant mutations to voltage-gated ion channels, called channelopathies, alter ion channel function, properties of ionic currents, and neuronal firing. The effects of ion channel mutations are routinely assessed and characterized as loss of function (LOF) or gain of function (GOF) at the level of ionic currents. However, emerging personalized medicine approaches based on LOF/GOF characterization have limited therapeutic success. Potential reasons are among others that the translation from this binary characterization to neuronal firing is currently not well-understood-especially when considering different neuronal cell types. In this study, we investigate the impact of neuronal cell type on the firing outcome of ion channel mutations. Methods To this end, we simulated a diverse collection of single-compartment, conductance-based neuron models that differed in their composition of ionic currents. We systematically analyzed the effects of changes in ion current properties on firing in different neuronal types. Additionally, we simulated the effects of known mutations in KCNA1 gene encoding the KV1.1 potassium channel subtype associated with episodic ataxia type 1 (EA1). Results These simulations revealed that the outcome of a given change in ion channel properties on neuronal excitability depends on neuron type, i.e., the properties and expression levels of the unaffected ionic currents. Discussion Consequently, neuron-type specific effects are vital to a full understanding of the effects of channelopathies on neuronal excitability and are an important step toward improving the efficacy and precision of personalized medicine approaches.
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Affiliation(s)
- Nils A. Koch
- Institute of Neurobiology, Faculty of Mathematics and Natural Sciences, University of Tübingen, Tübingen, Germany
- Bernstein Center for Computational Neuroscience Tübingen, Tübingen, Germany
| | - Lukas Sonnenberg
- Institute of Neurobiology, Faculty of Mathematics and Natural Sciences, University of Tübingen, Tübingen, Germany
- Bernstein Center for Computational Neuroscience Tübingen, Tübingen, Germany
| | - Ulrike B. S. Hedrich
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Stephan Lauxmann
- Institute of Neurobiology, Faculty of Mathematics and Natural Sciences, University of Tübingen, Tübingen, Germany
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Jan Benda
- Institute of Neurobiology, Faculty of Mathematics and Natural Sciences, University of Tübingen, Tübingen, Germany
- Bernstein Center for Computational Neuroscience Tübingen, Tübingen, Germany
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10
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Glasgow NG, Chen Y, Korngreen A, Kass RE, Urban NN. A biophysical and statistical modeling paradigm for connecting neural physiology and function. J Comput Neurosci 2023; 51:263-282. [PMID: 37140691 PMCID: PMC10182162 DOI: 10.1007/s10827-023-00847-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 02/10/2023] [Accepted: 02/16/2023] [Indexed: 05/05/2023]
Abstract
To understand single neuron computation, it is necessary to know how specific physiological parameters affect neural spiking patterns that emerge in response to specific stimuli. Here we present a computational pipeline combining biophysical and statistical models that provides a link between variation in functional ion channel expression and changes in single neuron stimulus encoding. More specifically, we create a mapping from biophysical model parameters to stimulus encoding statistical model parameters. Biophysical models provide mechanistic insight, whereas statistical models can identify associations between spiking patterns and the stimuli they encode. We used public biophysical models of two morphologically and functionally distinct projection neuron cell types: mitral cells (MCs) of the main olfactory bulb, and layer V cortical pyramidal cells (PCs). We first simulated sequences of action potentials according to certain stimuli while scaling individual ion channel conductances. We then fitted point process generalized linear models (PP-GLMs), and we constructed a mapping between the parameters in the two types of models. This framework lets us detect effects on stimulus encoding of changing an ion channel conductance. The computational pipeline combines models across scales and can be applied as a screen of channels, in any cell type of interest, to identify ways that channel properties influence single neuron computation.
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Affiliation(s)
- Nathan G Glasgow
- Department of Neurobiology and Center for Neuroscience, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
| | - Yu Chen
- Machine Learning Department, Carnegie Mellon University, Pittsburgh, PA, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Alon Korngreen
- The Leslie and Susan Gonda Interdisciplinary Brain Research Centre, Bar-Ilan University, Ramat Gan, Israel
- The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat Gan, Israel
| | - Robert E Kass
- Machine Learning Department, Carnegie Mellon University, Pittsburgh, PA, USA.
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA.
- Department of Statistics, Carnegie Mellon University, Pittsburgh, PA, USA.
| | - Nathan N Urban
- Department of Biological Sciences, Lehigh University, Bethlehem, PA, USA
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11
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Stöber TM, Batulin D, Triesch J, Narayanan R, Jedlicka P. Degeneracy in epilepsy: multiple routes to hyperexcitable brain circuits and their repair. Commun Biol 2023; 6:479. [PMID: 37137938 PMCID: PMC10156698 DOI: 10.1038/s42003-023-04823-0] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 04/06/2023] [Indexed: 05/05/2023] Open
Abstract
Due to its complex and multifaceted nature, developing effective treatments for epilepsy is still a major challenge. To deal with this complexity we introduce the concept of degeneracy to the field of epilepsy research: the ability of disparate elements to cause an analogous function or malfunction. Here, we review examples of epilepsy-related degeneracy at multiple levels of brain organisation, ranging from the cellular to the network and systems level. Based on these insights, we outline new multiscale and population modelling approaches to disentangle the complex web of interactions underlying epilepsy and to design personalised multitarget therapies.
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Affiliation(s)
- Tristan Manfred Stöber
- Frankfurt Institute for Advanced Studies, 60438, Frankfurt am Main, Germany
- Institute for Neural Computation, Faculty of Computer Science, Ruhr University Bochum, 44801, Bochum, Germany
- Epilepsy Center Frankfurt Rhine-Main, Department of Neurology, Goethe University, 60590, Frankfurt, Germany
| | - Danylo Batulin
- Frankfurt Institute for Advanced Studies, 60438, Frankfurt am Main, Germany
- CePTER - Center for Personalized Translational Epilepsy Research, Goethe University, 60590, Frankfurt, Germany
- Faculty of Computer Science and Mathematics, Goethe University, 60486, Frankfurt, Germany
| | - Jochen Triesch
- Frankfurt Institute for Advanced Studies, 60438, Frankfurt am Main, Germany
| | - Rishikesh Narayanan
- Cellular Neurophysiology Laboratory, Molecular Biophysics Unit, Indian Institute of Science, Bangalore, 560012, India
| | - Peter Jedlicka
- ICAR3R - Interdisciplinary Centre for 3Rs in Animal Research, Faculty of Medicine, Justus Liebig University Giessen, 35390, Giessen, Germany.
- Institute of Clinical Neuroanatomy, Neuroscience Center, Goethe University, 60590, Frankfurt am Main, Germany.
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12
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Zang Y, Marder E. Neuronal morphology enhances robustness to perturbations of channel densities. Proc Natl Acad Sci U S A 2023; 120:e2219049120. [PMID: 36787352 PMCID: PMC9974411 DOI: 10.1073/pnas.2219049120] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 01/14/2023] [Indexed: 02/15/2023] Open
Abstract
Biological neurons show significant cell-to-cell variability but have the striking ability to maintain their key firing properties in the face of unpredictable perturbations and stochastic noise. Using a population of multi-compartment models consisting of soma, neurites, and axon for the lateral pyloric neuron in the crab stomatogastric ganglion, we explore how rebound bursting is preserved when the 14 channel conductances in each model are all randomly varied. The coupling between the axon and other compartments is critical for the ability of the axon to spike during bursts and consequently determines the set of successful solutions. When the coupling deviates from a biologically realistic range, the neuronal tolerance of conductance variations is lessened. Thus, the gross morphological features of these neurons enhance their robustness to perturbations of channel densities and expand the space of individual variability that can maintain a desired output pattern.
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Affiliation(s)
- Yunliang Zang
- Volen Center, Brandeis University, Waltham, MA02454
- Department of Biology, Brandeis University, Waltham, MA02454
| | - Eve Marder
- Volen Center, Brandeis University, Waltham, MA02454
- Department of Biology, Brandeis University, Waltham, MA02454
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13
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Rathour RK, Kaphzan H. Voltage-Gated Ion Channels and the Variability in Information Transfer. Front Cell Neurosci 2022; 16:906313. [PMID: 35936503 PMCID: PMC9352938 DOI: 10.3389/fncel.2022.906313] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 06/24/2022] [Indexed: 11/13/2022] Open
Abstract
The prerequisites for neurons to function within a circuit and be able to contain and transfer information efficiently and reliably are that they need to be homeostatically stable and fire within a reasonable range, characteristics that are governed, among others, by voltage-gated ion channels (VGICs). Nonetheless, neurons entail large variability in the expression levels of VGICs and their corresponding intrinsic properties, but the role of this variability in information transfer is not fully known. In this study, we aimed to investigate how this variability of VGICs affects information transfer. For this, we used a previously derived population of neuronal model neurons, each with the variable expression of five types of VGICs, fast Na+, delayed rectifier K+, A-type K+, T-type Ca++, and HCN channels. These analyses showed that the model neurons displayed variability in mutual information transfer, measured as the capability of neurons to successfully encode incoming synaptic information in output firing frequencies. Likewise, variability in the expression of VGICs caused variability in EPSPs and IPSPs amplitudes, reflected in the variability of output firing frequencies. Finally, using the virtual knockout methodology, we show that among the ion channels tested, the A-type K+ channel is the major regulator of information processing and transfer.
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14
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Schneider AC, Itani O, Bucher D, Nadim F. Neuromodulation reduces interindividual variability of neuronal output. eNeuro 2022; 9:ENEURO.0166-22.2022. [PMID: 35853725 PMCID: PMC9361792 DOI: 10.1523/eneuro.0166-22.2022] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 05/27/2022] [Accepted: 06/06/2022] [Indexed: 11/24/2022] Open
Abstract
In similar states, neural circuits produce similar outputs across individuals despite substantial interindividual variability in neuronal ionic conductances and synapses. Circuit states are largely shaped by neuromodulators that tune ionic conductances. It is therefore possible that, in addition to producing flexible circuit output, neuromodulators also contribute to output similarity despite varying ion channel expression. We studied whether neuromodulation at saturating concentrations can increase the output similarity of a single identified neuron across individual animals. Using the LP neuron of the crab stomatogastric ganglion (STG), we compared the variability of f-I curves and rebound properties in the presence of neuropeptides. The two neuropeptides we used converge to activate the same target current, which increases neuronal excitability. Output variability was lower in the presence of the neuropeptides, regardless of whether the neuropeptides significantly changed the mean of the corresponding parameter or not. However, the addition of the second neuropeptide did not add further to the reduction of variability. With a family of computational LP-like models, we explored how increased excitability and target variability contribute to output similarity and found two mechanisms: Saturation of the responses and a differential increase in baseline activity. Saturation alone can reduce the interindividual variability only if the population shares a similar ceiling for the responses. In contrast, reduction of variability due to the increase in baseline activity is independent of ceiling effects.Significance StatementThe activity of single neurons and neural circuits can be very similar across individuals even though the ionic currents underlying activity are variable. The mechanisms that compensate for the underlying variability and promote output similarity are poorly understood but may involve neuromodulation. Using an identified neuron, we show that neuropeptide modulation of excitability can reduce interindividual variability of response properties at a single-neuron level in two ways. First, the neuropeptide increases baseline excitability in a differential manner, resulting in similar response thresholds. Second, the neuropeptide increases excitability towards a shared saturation level, promoting similar maximal firing rates across individuals. Such tuning of neuronal excitability could be an important mechanism compensating for interindividual variability of ion channel expression.
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Affiliation(s)
- Anna C Schneider
- Federated Department of Biological Sciences, New Jersey Institute of Technology and Rutgers University, Newark, NJ 07102
| | - Omar Itani
- Federated Department of Biological Sciences, New Jersey Institute of Technology and Rutgers University, Newark, NJ 07102
| | - Dirk Bucher
- Federated Department of Biological Sciences, New Jersey Institute of Technology and Rutgers University, Newark, NJ 07102
| | - Farzan Nadim
- Federated Department of Biological Sciences, New Jersey Institute of Technology and Rutgers University, Newark, NJ 07102
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15
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Chen Z, Terman DH, Travers SP, Travers JB. Regulation of Rostral Nucleus of the Solitary Tract Responses to Afferent Input by A-type K+ Current. Neuroscience 2022; 495:115-125. [PMID: 35659639 PMCID: PMC9253083 DOI: 10.1016/j.neuroscience.2022.05.036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Revised: 05/10/2022] [Accepted: 05/30/2022] [Indexed: 11/20/2022]
Abstract
Responses in the rostral (gustatory) nucleus of the solitary tract (rNST) are modified by synaptic interactions within the nucleus and the constitutive membrane properties of the neurons themselves. The potassium current IA is one potential source of modulation. In the caudal NST, projection neurons with IA show lower fidelity to afferent stimulation compared to cells without. We explored the role of an A-type K+ current (IA) in modulating the response to afferent stimulation and GABA-mediated inhibition in the rNST using whole cell patch clamp recording in transgenic mice that expressed channelrhodopsin (ChR2 H134R) in GABAergic neurons. The presence of IA was determined in current clamp and the response to electrical stimulation of afferent fibers in the solitary tract was assessed before and after treatment with the specific Kv4 channel blocker AmmTX3. Blocking IA significantly increased the response to afferent stimulation by 53%. Using dynamic clamp to create a synthetic IA conductance, we demonstrated a significant 14% decrease in responsiveness to afferent stimulation in cells lacking IA. Because IA reduced excitability and is hyperpolarization-sensitive, we examined whether IA contributed to the inhibition resulting from optogenetic release of GABA. Although blocking IA decreased the percent suppression induced by GABA, this effect was attributable to the increased responsiveness resulting from AmmTX3, not to a change in the absolute magnitude of suppression. We conclude that rNST responses to afferent input are regulated independently by IA and GABA.
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Affiliation(s)
- Z Chen
- Division of Biosciences, Ohio State University, United States
| | - D H Terman
- Department of Mathematics, Ohio State University, United States
| | - S P Travers
- Division of Biosciences, Ohio State University, United States
| | - J B Travers
- Division of Biosciences, Ohio State University, United States.
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16
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Jedlicka P, Bird AD, Cuntz H. Pareto optimality, economy-effectiveness trade-offs and ion channel degeneracy: improving population modelling for single neurons. Open Biol 2022; 12:220073. [PMID: 35857898 PMCID: PMC9277232 DOI: 10.1098/rsob.220073] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
Neurons encounter unavoidable evolutionary trade-offs between multiple tasks. They must consume as little energy as possible while effectively fulfilling their functions. Cells displaying the best performance for such multi-task trade-offs are said to be Pareto optimal, with their ion channel configurations underpinning their functionality. Ion channel degeneracy, however, implies that multiple ion channel configurations can lead to functionally similar behaviour. Therefore, instead of a single model, neuroscientists often use populations of models with distinct combinations of ionic conductances. This approach is called population (database or ensemble) modelling. It remains unclear, which ion channel parameters in the vast population of functional models are more likely to be found in the brain. Here we argue that Pareto optimality can serve as a guiding principle for addressing this issue by helping to identify the subpopulations of conductance-based models that perform best for the trade-off between economy and functionality. In this way, the high-dimensional parameter space of neuronal models might be reduced to geometrically simple low-dimensional manifolds, potentially explaining experimentally observed ion channel correlations. Conversely, Pareto inference might also help deduce neuronal functions from high-dimensional Patch-seq data. In summary, Pareto optimality is a promising framework for improving population modelling of neurons and their circuits.
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Affiliation(s)
- Peter Jedlicka
- ICAR3R - Interdisciplinary Centre for 3Rs in Animal Research, Faculty of Medicine, Justus-Liebig-University, Giessen, Germany,Institute of Clinical Neuroanatomy, Neuroscience Center, Goethe University, Frankfurt/Main, Germany,Frankfurt Institute for Advanced Studies, Frankfurt am Main, Germany
| | - Alexander D. Bird
- ICAR3R - Interdisciplinary Centre for 3Rs in Animal Research, Faculty of Medicine, Justus-Liebig-University, Giessen, Germany,Frankfurt Institute for Advanced Studies, Frankfurt am Main, Germany,Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt am Main, Germany
| | - Hermann Cuntz
- Frankfurt Institute for Advanced Studies, Frankfurt am Main, Germany,Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt am Main, Germany
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17
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Yang J, Shakil H, Ratté S, Prescott SA. Minimal requirements for a neuron to co-regulate many properties and the implications for ion channel correlations and robustness. eLife 2022; 11:72875. [PMID: 35293858 PMCID: PMC8986315 DOI: 10.7554/elife.72875] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Accepted: 03/03/2022] [Indexed: 11/13/2022] Open
Abstract
Neurons regulate their excitability by adjusting their ion channel levels. Degeneracy – achieving equivalent outcomes (excitability) using different solutions (channel combinations) – facilitates this regulation by enabling a disruptive change in one channel to be offset by compensatory changes in other channels. But neurons must coregulate many properties. Pleiotropy – the impact of one channel on more than one property – complicates regulation because a compensatory ion channel change that restores one property to its target value often disrupts other properties. How then does a neuron simultaneously regulate multiple properties? Here, we demonstrate that of the many channel combinations producing the target value for one property (the single-output solution set), few combinations produce the target value for other properties. Combinations producing the target value for two or more properties (the multioutput solution set) correspond to the intersection between single-output solution sets. Properties can be effectively coregulated only if the number of adjustable channels (nin) exceeds the number of regulated properties (nout). Ion channel correlations emerge during homeostatic regulation when the dimensionality of solution space (nin − nout) is low. Even if each property can be regulated to its target value when considered in isolation, regulation as a whole fails if single-output solution sets do not intersect. Our results also highlight that ion channels must be coadjusted with different ratios to regulate different properties, which suggests that each error signal drives modulatory changes independently, despite those changes ultimately affecting the same ion channels.
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Affiliation(s)
- Jane Yang
- Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Canada
| | - Husain Shakil
- Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Canada
| | - Stéphanie Ratté
- Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Canada
| | - Steven Alec Prescott
- Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Canada
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18
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Marder E, Rue MCP. From the Neuroscience of Individual Variability to Climate Change. J Neurosci 2021; 41:10213-10221. [PMID: 34753741 PMCID: PMC8672684 DOI: 10.1523/jneurosci.1261-21.2021] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Revised: 10/28/2021] [Accepted: 11/01/2021] [Indexed: 11/21/2022] Open
Abstract
Years of basic neuroscience on the modulation of the small circuits found in the crustacean stomatogastric ganglion have led us to study the effects of temperature on the motor patterns produced by the stomatogastric ganglion. While the impetus for this work was the study of individual variability in the parameters determining intrinsic and synaptic conductances, we are confronting substantial fluctuations in the stability of the networks to extreme temperature; these may correlate with changes in ocean temperature. Interestingly, when studied under control conditions, these wild-caught animals appear to be unchanged, but it is only when challenged by extreme temperatures that we reveal the consequences of warming oceans.
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Affiliation(s)
- Eve Marder
- Volen Center and Biology Department, Brandeis University, Waltham, Massachusetts 02454
| | - Mara C P Rue
- Volen Center and Biology Department, Brandeis University, Waltham, Massachusetts 02454
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19
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Abdelrahman NY, Vasilaki E, Lin AC. Compensatory variability in network parameters enhances memory performance in the Drosophila mushroom body. Proc Natl Acad Sci U S A 2021; 118:e2102158118. [PMID: 34845010 PMCID: PMC8670477 DOI: 10.1073/pnas.2102158118] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/06/2021] [Indexed: 11/18/2022] Open
Abstract
Neural circuits use homeostatic compensation to achieve consistent behavior despite variability in underlying intrinsic and network parameters. However, it remains unclear how compensation regulates variability across a population of the same type of neurons within an individual and what computational benefits might result from such compensation. We address these questions in the Drosophila mushroom body, the fly's olfactory memory center. In a computational model, we show that under sparse coding conditions, memory performance is degraded when the mushroom body's principal neurons, Kenyon cells (KCs), vary realistically in key parameters governing their excitability. However, memory performance is rescued while maintaining realistic variability if parameters compensate for each other to equalize KC average activity. Such compensation can be achieved through both activity-dependent and activity-independent mechanisms. Finally, we show that correlations predicted by our model's compensatory mechanisms appear in the Drosophila hemibrain connectome. These findings reveal compensatory variability in the mushroom body and describe its computational benefits for associative memory.
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Affiliation(s)
- Nada Y Abdelrahman
- School of Biosciences, University of Sheffield, Sheffield S10 2TN, United Kingdom
- Department of Computer Science, University of Sheffield, Sheffield S1 4DP, United Kingdom
- Neuroscience Institute, University of Sheffield, Sheffield S10 2TN, United Kingdom
| | - Eleni Vasilaki
- Department of Computer Science, University of Sheffield, Sheffield S1 4DP, United Kingdom
- Neuroscience Institute, University of Sheffield, Sheffield S10 2TN, United Kingdom
| | - Andrew C Lin
- School of Biosciences, University of Sheffield, Sheffield S10 2TN, United Kingdom;
- Neuroscience Institute, University of Sheffield, Sheffield S10 2TN, United Kingdom
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20
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Kamaleddin MA. Degeneracy in the nervous system: from neuronal excitability to neural coding. Bioessays 2021; 44:e2100148. [PMID: 34791666 DOI: 10.1002/bies.202100148] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Revised: 09/26/2021] [Accepted: 09/28/2021] [Indexed: 02/04/2023]
Abstract
Degeneracy is ubiquitous across biological systems where structurally different elements can yield a similar outcome. Degeneracy is of particular interest in neuroscience too. On the one hand, degeneracy confers robustness to the nervous system and facilitates evolvability: Different elements provide a backup plan for the system in response to any perturbation or disturbance. On the other, a difficulty in the treatment of some neurological disorders such as chronic pain is explained in light of different elements all of which contribute to the pathological behavior of the system. Under these circumstances, targeting a specific element is ineffective because other elements can compensate for this modulation. Understanding degeneracy in the physiological context explains its beneficial role in the robustness of neural circuits. Likewise, understanding degeneracy in the pathological context opens new avenues of discovery to find more effective therapies.
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Affiliation(s)
- Mohammad Amin Kamaleddin
- Institute of Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada.,Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario, Canada
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21
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Frequency-Dependent Action of Neuromodulation. eNeuro 2021; 8:ENEURO.0338-21.2021. [PMID: 34593519 PMCID: PMC8584230 DOI: 10.1523/eneuro.0338-21.2021] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Revised: 09/21/2021] [Accepted: 09/23/2021] [Indexed: 11/21/2022] Open
Abstract
In oscillatory circuits, some actions of neuromodulators depend on the oscillation frequency. However, the mechanisms are poorly understood. We explored this problem by characterizing neuromodulation of the lateral pyloric (LP) neuron of the crab stomatogastric ganglion (STG). Many peptide modulators, including proctolin, activate the same ionic current (IMI) in STG neurons. Because IMI is fast and non-inactivating, its peak level does not depend on the temporal properties of neuronal activity. We found, however, that the amplitude and peak time of the proctolin-activated current in LP is frequency dependent. Because frequency affects the rate of voltage change, we measured these currents with voltage ramps of different slopes and found that proctolin activated two kinetically distinct ionic currents: the known IMI, whose amplitude is independent of ramp slope or direction, and an inactivating current (IMI-T), which was only activated by positive ramps and whose amplitude increased with increasing ramp slope. Using a conductance-based model we found that IMI and IMI-T make distinct contributions to the bursting activity, with IMI increasing the excitability, and IMI-T regulating the burst onset by modifying the postinhibitory rebound in a frequency-dependent manner. The voltage dependence and partial calcium permeability of IMI-T is similar to other characterized neuromodulator-activated currents in this system, suggesting that these are isoforms of the same channel. Our computational model suggests that calcium permeability may allow this current to also activate the large calcium-dependent potassium current in LP, providing an additional mechanism to regulate burst termination. These results demonstrate a mechanism for frequency-dependent actions of neuromodulators.
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22
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Sinha M, Narayanan R. Active Dendrites and Local Field Potentials: Biophysical Mechanisms and Computational Explorations. Neuroscience 2021; 489:111-142. [PMID: 34506834 PMCID: PMC7612676 DOI: 10.1016/j.neuroscience.2021.08.035] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Revised: 08/30/2021] [Accepted: 08/31/2021] [Indexed: 10/27/2022]
Abstract
Neurons and glial cells are endowed with membranes that express a rich repertoire of ion channels, transporters, and receptors. The constant flux of ions across the neuronal and glial membranes results in voltage fluctuations that can be recorded from the extracellular matrix. The high frequency components of this voltage signal contain information about the spiking activity, reflecting the output from the neurons surrounding the recording location. The low frequency components of the signal, referred to as the local field potential (LFP), have been traditionally thought to provide information about the synaptic inputs that impinge on the large dendritic trees of various neurons. In this review, we discuss recent computational and experimental studies pointing to a critical role of several active dendritic mechanisms that can influence the genesis and the location-dependent spectro-temporal dynamics of LFPs, spanning different brain regions. We strongly emphasize the need to account for the several fast and slow dendritic events and associated active mechanisms - including gradients in their expression profiles, inter- and intra-cellular spatio-temporal interactions spanning neurons and glia, heterogeneities and degeneracy across scales, neuromodulatory influences, and activitydependent plasticity - towards gaining important insights about the origins of LFP under different behavioral states in health and disease. We provide simple but essential guidelines on how to model LFPs taking into account these dendritic mechanisms, with detailed methodology on how to account for various heterogeneities and electrophysiological properties of neurons and synapses while studying LFPs.
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Affiliation(s)
- Manisha Sinha
- Cellular Neurophysiology Laboratory, Molecular Biophysics Unit, Indian Institute of Science, Bangalore, Karnataka 560012, India
| | - Rishikesh Narayanan
- Cellular Neurophysiology Laboratory, Molecular Biophysics Unit, Indian Institute of Science, Bangalore, Karnataka 560012, India.
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23
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Roussel Y, Gaudreau SF, Kacer ER, Sengupta M, Bui TV. Modeling spinal locomotor circuits for movements in developing zebrafish. eLife 2021; 10:e67453. [PMID: 34473059 PMCID: PMC8492062 DOI: 10.7554/elife.67453] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2021] [Accepted: 09/01/2021] [Indexed: 01/16/2023] Open
Abstract
Many spinal circuits dedicated to locomotor control have been identified in the developing zebrafish. How these circuits operate together to generate the various swimming movements during development remains to be clarified. In this study, we iteratively built models of developing zebrafish spinal circuits coupled to simplified musculoskeletal models that reproduce coiling and swimming movements. The neurons of the models were based upon morphologically or genetically identified populations in the developing zebrafish spinal cord. We simulated intact spinal circuits as well as circuits with silenced neurons or altered synaptic transmission to better understand the role of specific spinal neurons. Analysis of firing patterns and phase relationships helped to identify possible mechanisms underlying the locomotor movements of developing zebrafish. Notably, our simulations demonstrated how the site and the operation of rhythm generation could transition between coiling and swimming. The simulations also underlined the importance of contralateral excitation to multiple tail beats. They allowed us to estimate the sensitivity of spinal locomotor networks to motor command amplitude, synaptic weights, length of ascending and descending axons, and firing behavior. These models will serve as valuable tools to test and further understand the operation of spinal circuits for locomotion.
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Affiliation(s)
- Yann Roussel
- Brain and Mind Research Institute, Centre for Neural Dynamics, Department of Biology, University of OttawaOttawaCanada
- Blue Brain Project, École Polytechnique Fédérale de LausanneGenèveSwitzerland
| | - Stephanie F Gaudreau
- Brain and Mind Research Institute, Centre for Neural Dynamics, Department of Biology, University of OttawaOttawaCanada
| | - Emily R Kacer
- Brain and Mind Research Institute, Centre for Neural Dynamics, Department of Biology, University of OttawaOttawaCanada
| | - Mohini Sengupta
- Washington University School of Medicine, Department of NeuroscienceSt LouisUnited States
| | - Tuan V Bui
- Brain and Mind Research Institute, Centre for Neural Dynamics, Department of Biology, University of OttawaOttawaCanada
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24
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Mishra P, Narayanan R. Ion-channel degeneracy: Multiple ion channels heterogeneously regulate intrinsic physiology of rat hippocampal granule cells. Physiol Rep 2021; 9:e14963. [PMID: 34342171 PMCID: PMC8329439 DOI: 10.14814/phy2.14963] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2021] [Revised: 06/13/2021] [Accepted: 06/21/2021] [Indexed: 01/09/2023] Open
Abstract
Degeneracy, the ability of multiple structural components to elicit the same characteristic functional properties, constitutes an elegant mechanism for achieving biological robustness. In this study, we sought electrophysiological signatures for the expression of ion-channel degeneracy in the emergence of intrinsic properties of rat hippocampal granule cells. We measured the impact of four different ion-channel subtypes-hyperpolarization-activated cyclic-nucleotide-gated (HCN), barium-sensitive inward rectifier potassium (Kir ), tertiapin-Q-sensitive inward rectifier potassium, and persistent sodium (NaP) channels-on 21 functional measurements employing pharmacological agents, and report electrophysiological data on two characteristic signatures for the expression of ion-channel degeneracy in granule cells. First, the blockade of a specific ion-channel subtype altered several, but not all, functional measurements. Furthermore, any given functional measurement was altered by the blockade of many, but not all, ion-channel subtypes. Second, the impact of blocking each ion-channel subtype manifested neuron-to-neuron variability in the quantum of changes in the electrophysiological measurements. Specifically, we found that blocking HCN or Ba-sensitive Kir channels enhanced action potential firing rate, but blockade of NaP channels reduced firing rate of granule cells. Subthreshold measures of granule cell intrinsic excitability (input resistance, temporal summation, and impedance amplitude) were enhanced by blockade of HCN or Ba-sensitive Kir channels, but were not significantly altered by NaP channel blockade. We confirmed that the HCN and Ba-sensitive Kir channels independently altered sub- and suprathreshold properties of granule cells through sequential application of pharmacological agents that blocked these channels. Finally, we found that none of the sub- or suprathreshold measurements of granule cells were significantly altered upon treatment with tertiapin-Q. Together, the heterogeneous many-to-many mapping between ion channels and single-neuron intrinsic properties emphasizes the need to account for ion-channel degeneracy in cellular- and network-scale physiology.
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Affiliation(s)
- Poonam Mishra
- Cellular Neurophysiology LaboratoryMolecular Biophysics UnitIndian Institute of ScienceBangaloreIndia
| | - Rishikesh Narayanan
- Cellular Neurophysiology LaboratoryMolecular Biophysics UnitIndian Institute of ScienceBangaloreIndia
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25
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Boeri J, Meunier C, Le Corronc H, Branchereau P, Timofeeva Y, Lejeune FX, Mouffle C, Arulkandarajah H, Mangin JM, Legendre P, Czarnecki A. Two opposite voltage-dependent currents control the unusual early development pattern of embryonic Renshaw cell electrical activity. eLife 2021; 10:62639. [PMID: 33899737 PMCID: PMC8139835 DOI: 10.7554/elife.62639] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Accepted: 04/24/2021] [Indexed: 11/25/2022] Open
Abstract
Renshaw cells (V1R) are excitable as soon as they reach their final location next to the spinal motoneurons and are functionally heterogeneous. Using multiple experimental approaches, in combination with biophysical modeling and dynamical systems theory, we analyzed, for the first time, the mechanisms underlying the electrophysiological properties of V1R during early embryonic development of the mouse spinal cord locomotor networks (E11.5–E16.5). We found that these interneurons are subdivided into several functional clusters from E11.5 and then display an unexpected transitory involution process during which they lose their ability to sustain tonic firing. We demonstrated that the essential factor controlling the diversity of the discharge pattern of embryonic V1R is the ratio of a persistent sodium conductance to a delayed rectifier potassium conductance. Taken together, our results reveal how a simple mechanism, based on the synergy of two voltage-dependent conductances that are ubiquitous in neurons, can produce functional diversity in embryonic V1R and control their early developmental trajectory.
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Affiliation(s)
- Juliette Boeri
- INSERM, UMR_S 1130, CNRS, UMR 8246, Neuroscience Paris Seine, Institute of Biology Paris Seine, Sorbonne Univ, Paris, France
| | - Claude Meunier
- Centre de Neurosciences Intégratives et Cognition, CNRS UMR 8002, Institut Neurosciences et Cognition, Université de Paris, Paris, France
| | - Hervé Le Corronc
- INSERM, UMR_S 1130, CNRS, UMR 8246, Neuroscience Paris Seine, Institute of Biology Paris Seine, Sorbonne Univ, Paris, France.,Univ Angers, Angers, France
| | | | - Yulia Timofeeva
- Department of Computer Science and Centre for Complexity Science, University of Warwick, Coventry, United Kingdom.,Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - François-Xavier Lejeune
- Institut du Cerveau et de la Moelle Epinière, Centre de Recherche CHU Pitié-Salpétrière, INSERM, U975, CNRS, UMR 7225, Sorbonne Univ, Paris, France
| | - Christine Mouffle
- INSERM, UMR_S 1130, CNRS, UMR 8246, Neuroscience Paris Seine, Institute of Biology Paris Seine, Sorbonne Univ, Paris, France
| | - Hervé Arulkandarajah
- INSERM, UMR_S 1130, CNRS, UMR 8246, Neuroscience Paris Seine, Institute of Biology Paris Seine, Sorbonne Univ, Paris, France
| | - Jean Marie Mangin
- INSERM, UMR_S 1130, CNRS, UMR 8246, Neuroscience Paris Seine, Institute of Biology Paris Seine, Sorbonne Univ, Paris, France
| | - Pascal Legendre
- INSERM, UMR_S 1130, CNRS, UMR 8246, Neuroscience Paris Seine, Institute of Biology Paris Seine, Sorbonne Univ, Paris, France
| | - Antonny Czarnecki
- INSERM, UMR_S 1130, CNRS, UMR 8246, Neuroscience Paris Seine, Institute of Biology Paris Seine, Sorbonne Univ, Paris, France.,Univ. Bordeaux, CNRS, EPHE, INCIA, Bordeaux, France
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26
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Goaillard JM, Marder E. Ion Channel Degeneracy, Variability, and Covariation in Neuron and Circuit Resilience. Annu Rev Neurosci 2021; 44:335-357. [PMID: 33770451 DOI: 10.1146/annurev-neuro-092920-121538] [Citation(s) in RCA: 85] [Impact Index Per Article: 21.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The large number of ion channels found in all nervous systems poses fundamental questions concerning how the characteristic intrinsic properties of single neurons are determined by the specific subsets of channels they express. All neurons display many different ion channels with overlapping voltage- and time-dependent properties. We speculate that these overlapping properties promote resilience in neuronal function. Individual neurons of the same cell type show variability in ion channel conductance densities even though they can generate reliable and similar behavior. This complicates a simple assignment of function to any conductance and is associated with variable responses of neurons of the same cell type to perturbations, deletions, and pharmacological manipulation. Ion channel genes often show strong positively correlated expression, which may result from the molecular and developmental rules that determine which ion channels are expressed in a given cell type.
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Affiliation(s)
| | - Eve Marder
- Volen Center and Department of Biology, Brandeis University, Waltham, Massachusetts 02454, USA;
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27
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Mishra P, Narayanan R. Ion-channel regulation of response decorrelation in a heterogeneous multi-scale model of the dentate gyrus. CURRENT RESEARCH IN NEUROBIOLOGY 2021; 2:100007. [PMID: 33997798 PMCID: PMC7610774 DOI: 10.1016/j.crneur.2021.100007] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
Heterogeneities in biological neural circuits manifest in afferent connectivity as well as in local-circuit components such as neuronal excitability, neural structure and local synaptic strengths. The expression of adult neurogenesis in the dentate gyrus (DG) amplifies local-circuit heterogeneities and guides heterogeneities in afferent connectivity. How do neurons and their networks endowed with these distinct forms of heterogeneities respond to perturbations to individual ion channels, which are known to change under several physiological and pathophysiological conditions? We sequentially traversed the ion channels-neurons-network scales and assessed the impact of eliminating individual ion channels on conductance-based neuronal and network models endowed with disparate local-circuit and afferent heterogeneities. We found that many ion channels differentially contributed to specific neuronal or network measurements, and the elimination of any given ion channel altered several functional measurements. We then quantified the impact of ion-channel elimination on response decorrelation, a well-established metric to assess the ability of neurons in a network to convey complementary information, in DG networks endowed with different forms of heterogeneities. Notably, we found that networks constructed with structurally immature neurons exhibited functional robustness, manifesting as minimal changes in response decorrelation in the face of ion-channel elimination. Importantly, the average change in output correlation was dependent on the eliminated ion channel but invariant to input correlation. Our analyses suggest that neurogenesis-driven structural heterogeneities could assist the DG network in providing functional resilience to molecular perturbations. Perturbations at one scale result in a cascading impact on physiology across scales. Heterogeneous multi-scale models used to assess the impact of ion-channel deletion. Mapping of structural components to functional outcomes is many-to-many. Differential & variable impact of ion channel deletion on response decorrelation. Neurogenesis-induced structural heterogeneity confers resilience to perturbations.
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Affiliation(s)
- Poonam Mishra
- Cellular Neurophysiology Laboratory, Molecular Biophysics Unit, Indian Institute of Science, Bangalore 560012, India
| | - Rishikesh Narayanan
- Cellular Neurophysiology Laboratory, Molecular Biophysics Unit, Indian Institute of Science, Bangalore 560012, India
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28
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Daou A, Margoliash D. Intrinsic plasticity and birdsong learning. Neurobiol Learn Mem 2021; 180:107407. [PMID: 33631346 DOI: 10.1016/j.nlm.2021.107407] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Revised: 10/28/2020] [Accepted: 02/11/2021] [Indexed: 10/22/2022]
Abstract
Although information processing and storage in the brain is thought to be primarily orchestrated by synaptic plasticity, other neural mechanisms such as intrinsic plasticity are available. While a number of recent studies have described the plasticity of intrinsic excitability in several types of neurons, the significance of non-synaptic mechanisms in memory and learning remains elusive. After reviewing plasticity of intrinsic excitation in relation to learning and homeostatic mechanisms, we focus on the intrinsic properties of a class of basal-ganglia projecting song system neurons in zebra finch, how these related to each bird's unique learned song, how these properties change over development, and how they are maintained dynamically to rapidly change in response to auditory feedback perturbations. We place these results in the broader theme of learning and changes in intrinsic properties, emphasizing the computational implications of this form of plasticity, which are distinct from synaptic plasticity. The results suggest that exploring reciprocal interactions between intrinsic and network properties will be a fruitful avenue for understanding mechanisms of birdsong learning.
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Affiliation(s)
- Arij Daou
- University of Chicago, United States
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29
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Ratliff J, Franci A, Marder E, O'Leary T. Neuronal oscillator robustness to multiple global perturbations. Biophys J 2021; 120:1454-1468. [PMID: 33610580 PMCID: PMC8105708 DOI: 10.1016/j.bpj.2021.01.038] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Revised: 12/07/2020] [Accepted: 01/07/2021] [Indexed: 11/29/2022] Open
Abstract
Neuronal activity depends on ion channels and biophysical processes that are strongly and differentially sensitive to physical variables such as temperature and pH. Nonetheless, neuronal oscillators can be surprisingly resilient to perturbations in these variables. We study a three-neuron pacemaker ensemble that drives the pyloric rhythm of the crab, Cancer borealis. These crabs routinely experience a number of global perturbations, including changes in temperature and pH. Although pyloric oscillations are robust to such changes, for sufficiently large deviations the rhythm reversibly breaks down. As temperature increases beyond a tipping point, oscillators transition to silence. Acidic pH deviations also show tipping points, with a reliable transition first to tonic spiking, then to silence. Surprisingly, robustness to perturbations in pH only moderately affects temperature robustness. Consistent with high animal-to-animal variability in biophysical circuit parameters, tipping points in temperature and pH vary across animals. However, the ordering and discrete classes of transitions at critical points are conserved. This implies that qualitative oscillator dynamics are preserved across animals despite high quantitative parameter variability. A universal model of bursting dynamics predicts the existence of these transition types and the order in which they occur.
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Affiliation(s)
- Jacob Ratliff
- Dominick P Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, New York
| | - Alessio Franci
- Department of Mathematics, National Autonomous University of Mexico, Mexico City, Mexico
| | - Eve Marder
- Biology Department, Volen Center, Brandeis University, Waltham, Massachusetts.
| | - Timothy O'Leary
- Department of Engineering, University of Cambridge, Cambridge, United Kingdom.
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30
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Oesterle J, Behrens C, Schröder C, Hermann T, Euler T, Franke K, Smith RG, Zeck G, Berens P. Bayesian inference for biophysical neuron models enables stimulus optimization for retinal neuroprosthetics. eLife 2020; 9:e54997. [PMID: 33107821 PMCID: PMC7673784 DOI: 10.7554/elife.54997] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Accepted: 10/26/2020] [Indexed: 01/02/2023] Open
Abstract
While multicompartment models have long been used to study the biophysics of neurons, it is still challenging to infer the parameters of such models from data including uncertainty estimates. Here, we performed Bayesian inference for the parameters of detailed neuron models of a photoreceptor and an OFF- and an ON-cone bipolar cell from the mouse retina based on two-photon imaging data. We obtained multivariate posterior distributions specifying plausible parameter ranges consistent with the data and allowing to identify parameters poorly constrained by the data. To demonstrate the potential of such mechanistic data-driven neuron models, we created a simulation environment for external electrical stimulation of the retina and optimized stimulus waveforms to target OFF- and ON-cone bipolar cells, a current major problem of retinal neuroprosthetics.
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Affiliation(s)
- Jonathan Oesterle
- Institute for Ophthalmic Research, University of TübingenTübingenGermany
| | - Christian Behrens
- Institute for Ophthalmic Research, University of TübingenTübingenGermany
| | - Cornelius Schröder
- Institute for Ophthalmic Research, University of TübingenTübingenGermany
| | - Thoralf Hermann
- Naturwissenschaftliches und Medizinisches Institut an der Universität TübingenReutlingenGermany
| | - Thomas Euler
- Institute for Ophthalmic Research, University of TübingenTübingenGermany
- Center for Integrative Neuroscience, University of TübingenTübingenGermany
- Bernstein Center for Computational Neuroscience, University of TübingenTübingenGermany
| | - Katrin Franke
- Institute for Ophthalmic Research, University of TübingenTübingenGermany
- Bernstein Center for Computational Neuroscience, University of TübingenTübingenGermany
| | - Robert G Smith
- Department of Neuroscience, University of PennsylvaniaPhiladelphiaUnited States
| | - Günther Zeck
- Naturwissenschaftliches und Medizinisches Institut an der Universität TübingenReutlingenGermany
| | - Philipp Berens
- Institute for Ophthalmic Research, University of TübingenTübingenGermany
- Center for Integrative Neuroscience, University of TübingenTübingenGermany
- Bernstein Center for Computational Neuroscience, University of TübingenTübingenGermany
- Institute for Bioinformatics and Medical Informatics, University of TübingenTübingenGermany
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31
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Activity-dependent compensation of cell size is vulnerable to targeted deletion of ion channels. Sci Rep 2020; 10:15989. [PMID: 32994529 PMCID: PMC7524806 DOI: 10.1038/s41598-020-72977-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Accepted: 08/25/2020] [Indexed: 01/13/2023] Open
Abstract
In many species, excitable cells preserve their physiological properties despite significant variation in physical size across time and in a population. For example, neurons in crustacean central pattern generators generate similar firing patterns despite several-fold increases in size between juveniles and adults. This presents a biophysical problem because the electrical properties of cells are highly sensitive to membrane area and channel density. It is not known whether specific mechanisms exist to sense membrane area and adjust channel expression to keep a consistent channel density, or whether regulation mechanisms that sense activity alone are capable of compensating cell size. We show that destabilising effects of growth can be specifically compensated by feedback mechanism that senses average calcium influx and jointly regulate multiple conductances. However, we further show that this class of growth-compensating regulation schemes is necessarily sensitive to perturbations that alter the expression of subsets of ion channel types. Targeted perturbations of specific ion channels can trigger a pathological response of the regulation mechanism and a failure of homeostasis. Our findings suggest that physiological regulation mechanisms that confer robustness to growth may be specifically vulnerable to deletions or mutations that affect subsets of ion channels.
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32
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Gonçalves PJ, Lueckmann JM, Deistler M, Nonnenmacher M, Öcal K, Bassetto G, Chintaluri C, Podlaski WF, Haddad SA, Vogels TP, Greenberg DS, Macke JH. Training deep neural density estimators to identify mechanistic models of neural dynamics. eLife 2020; 9:e56261. [PMID: 32940606 PMCID: PMC7581433 DOI: 10.7554/elife.56261] [Citation(s) in RCA: 78] [Impact Index Per Article: 15.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Accepted: 09/16/2020] [Indexed: 01/27/2023] Open
Abstract
Mechanistic modeling in neuroscience aims to explain observed phenomena in terms of underlying causes. However, determining which model parameters agree with complex and stochastic neural data presents a significant challenge. We address this challenge with a machine learning tool which uses deep neural density estimators-trained using model simulations-to carry out Bayesian inference and retrieve the full space of parameters compatible with raw data or selected data features. Our method is scalable in parameters and data features and can rapidly analyze new data after initial training. We demonstrate the power and flexibility of our approach on receptive fields, ion channels, and Hodgkin-Huxley models. We also characterize the space of circuit configurations giving rise to rhythmic activity in the crustacean stomatogastric ganglion, and use these results to derive hypotheses for underlying compensation mechanisms. Our approach will help close the gap between data-driven and theory-driven models of neural dynamics.
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Affiliation(s)
- Pedro J Gonçalves
- Computational Neuroengineering, Department of Electrical and Computer Engineering, Technical University of MunichMunichGermany
- Max Planck Research Group Neural Systems Analysis, Center of Advanced European Studies and Research (caesar)BonnGermany
| | - Jan-Matthis Lueckmann
- Computational Neuroengineering, Department of Electrical and Computer Engineering, Technical University of MunichMunichGermany
- Max Planck Research Group Neural Systems Analysis, Center of Advanced European Studies and Research (caesar)BonnGermany
| | - Michael Deistler
- Computational Neuroengineering, Department of Electrical and Computer Engineering, Technical University of MunichMunichGermany
- Machine Learning in Science, Excellence Cluster Machine Learning, Tübingen UniversityTübingenGermany
| | - Marcel Nonnenmacher
- Computational Neuroengineering, Department of Electrical and Computer Engineering, Technical University of MunichMunichGermany
- Max Planck Research Group Neural Systems Analysis, Center of Advanced European Studies and Research (caesar)BonnGermany
- Model-Driven Machine Learning, Institute of Coastal Research, Helmholtz Centre GeesthachtGeesthachtGermany
| | - Kaan Öcal
- Max Planck Research Group Neural Systems Analysis, Center of Advanced European Studies and Research (caesar)BonnGermany
- Mathematical Institute, University of BonnBonnGermany
| | - Giacomo Bassetto
- Computational Neuroengineering, Department of Electrical and Computer Engineering, Technical University of MunichMunichGermany
- Max Planck Research Group Neural Systems Analysis, Center of Advanced European Studies and Research (caesar)BonnGermany
| | - Chaitanya Chintaluri
- Centre for Neural Circuits and Behaviour, University of OxfordOxfordUnited Kingdom
- Institute of Science and Technology AustriaKlosterneuburgAustria
| | - William F Podlaski
- Centre for Neural Circuits and Behaviour, University of OxfordOxfordUnited Kingdom
| | - Sara A Haddad
- Max Planck Institute for Brain ResearchFrankfurtGermany
| | - Tim P Vogels
- Centre for Neural Circuits and Behaviour, University of OxfordOxfordUnited Kingdom
- Institute of Science and Technology AustriaKlosterneuburgAustria
| | - David S Greenberg
- Computational Neuroengineering, Department of Electrical and Computer Engineering, Technical University of MunichMunichGermany
- Model-Driven Machine Learning, Institute of Coastal Research, Helmholtz Centre GeesthachtGeesthachtGermany
| | - Jakob H Macke
- Computational Neuroengineering, Department of Electrical and Computer Engineering, Technical University of MunichMunichGermany
- Max Planck Research Group Neural Systems Analysis, Center of Advanced European Studies and Research (caesar)BonnGermany
- Machine Learning in Science, Excellence Cluster Machine Learning, Tübingen UniversityTübingenGermany
- Max Planck Institute for Intelligent SystemsTübingenGermany
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33
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Ruffolo JA, McClellan AD. Modeling of lamprey reticulospinal neurons: multiple distinct parameter sets yield realistic simulations. J Neurophysiol 2020; 124:895-913. [PMID: 32697608 DOI: 10.1152/jn.00070.2020] [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: 11/22/2022] Open
Abstract
For the lamprey and other vertebrates, reticulospinal (RS) neurons project descending axons to the spinal cord and activate motor networks to initiate locomotion and other behaviors. In the present study, a biophysically detailed computer model of lamprey RS neurons was constructed consisting of three compartments: dendritic, somatic, and axon initial segment (AIS). All compartments included passive channels. In addition, the soma and AIS had fast potassium and sodium channels. The soma included three additional voltage-gated ion channels (slow sodium and high- and low-voltage-activated calcium) and calcium-activated potassium channels. An initial manually adjusted default parameter set, which was based, in part, on modified parameters from models of lamprey spinal neurons, generated simulations of single action potentials and repetitive firing that scored favorably (0.658; maximum = 0.964) compared with experimentally derived properties of lamprey RS neurons. Subsequently, a dual-annealing search paradigm identified 4,302 viable parameter sets at local maxima within parameter space that yielded higher scores than the default parameter set, including many with much higher scores of approximately 0.85-0.87 (i.e., ~30% improvement). In addition, 5- and 2-conductance grid searches identified a relatively large number of viable parameters sets for which significant correlations were present between maximum conductances for pairs of ion channels. The present results indicated that multiple model parameter sets ("solutions") generated action potentials and repetitive firing that mimicked many of the properties of lamprey RS neurons. To our knowledge, this is the first study to systematically explore parameter space for a biophysically detailed model of lamprey RS neurons.NEW & NOTEWORTHY A computer model of lamprey reticulospinal neurons with a default parameter set produced simulations of action potentials and repetitive firing that scored favorably compared with the properties of these neurons. A dual-annealing search algorithm explored ~50 million parameter sets and identified 4,302 distinct viable parameter sets within parameter space that yielded higher/much higher scores than the default parameter set. In addition, 5- and 2-conductance grid searches identified significant correlations between maximum conductances for pairs of ion channels.
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Affiliation(s)
- Jeffrey A Ruffolo
- Division of Biological Science, University of Missouri, Columbia, Missouri
| | - Andrew D McClellan
- Division of Biological Science, University of Missouri, Columbia, Missouri.,Interdisciplinary Neuroscience Program, University of Missouri, Columbia, Missouri
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Lindroos R, Hellgren Kotaleski J. Predicting complex spikes in striatal projection neurons of the direct pathway following neuromodulation by acetylcholine and dopamine. Eur J Neurosci 2020; 53:2117-2134. [DOI: 10.1111/ejn.14891] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Revised: 06/15/2020] [Accepted: 06/25/2020] [Indexed: 02/03/2023]
Affiliation(s)
- Robert Lindroos
- Department of Neuroscience Karolinska Institutet Stockholm Sweden
| | - Jeanette Hellgren Kotaleski
- Department of Neuroscience Karolinska Institutet Stockholm Sweden
- Science for Life Laboratory Department of Computational Science and Technology The Royal Institute of Technology Stockholm Sweden
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35
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He LS, Rue MCP, Morozova EO, Powell DJ, James EJ, Kar M, Marder E. Rapid adaptation to elevated extracellular potassium in the pyloric circuit of the crab, Cancer borealis. J Neurophysiol 2020; 123:2075-2089. [PMID: 32319837 DOI: 10.1152/jn.00135.2020] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023] Open
Abstract
Elevated potassium concentration ([K+]) is often used to alter excitability in neurons and networks by shifting the potassium equilibrium potential (EK) and, consequently, the resting membrane potential. We studied the effects of increased extracellular [K+] on the well-described pyloric circuit of the crab Cancer borealis. A 2.5-fold increase in extracellular [K+] (2.5×[K+]) depolarized pyloric dilator (PD) neurons and resulted in short-term loss of their normal bursting activity. This period of silence was followed within 5-10 min by the recovery of spiking and/or bursting activity during continued superfusion of 2.5×[K+] saline. In contrast, when PD neurons were pharmacologically isolated from pyloric presynaptic inputs, they exhibited no transient loss of spiking activity in 2.5×[K+], suggesting the presence of an acute inhibitory effect mediated by circuit interactions. Action potential threshold in PD neurons hyperpolarized during an hour-long exposure to 2.5×[K+] concurrent with the recovery of spiking and/or bursting activity. Thus the initial loss of activity appears to be mediated by synaptic interactions within the network, but the secondary adaptation depends on changes in the intrinsic excitability of the pacemaker neurons. The complex sequence of events in the responses of pyloric neurons to elevated [K+] demonstrates that electrophysiological recordings are necessary to determine both the transient and longer term effects of even modest alterations of K+ concentrations on neuronal activity.NEW & NOTEWORTHY Solutions with elevated extracellular potassium are commonly used as a depolarizing stimulus. We studied the effects of high potassium concentration ([K+]) on the pyloric circuit of the crab stomatogastric ganglion. A 2.5-fold increase in extracellular [K+] caused a transient loss of activity that was not due to depolarization block, followed by a rapid increase in excitability and recovery of spiking within minutes. This suggests that changing extracellular potassium can have complex and nonstationary effects on neuronal circuits.
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Affiliation(s)
- Lily S He
- Biology Department and Volen Center, Brandeis University, Waltham, Massachusetts
| | - Mara C P Rue
- Biology Department and Volen Center, Brandeis University, Waltham, Massachusetts
| | - Ekaterina O Morozova
- Biology Department and Volen Center, Brandeis University, Waltham, Massachusetts
| | - Daniel J Powell
- Biology Department and Volen Center, Brandeis University, Waltham, Massachusetts
| | - Eric J James
- Biology Department, Adelphi University, Garden City, New York
| | - Manaswini Kar
- Department of Neurobiology, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Eve Marder
- Biology Department and Volen Center, Brandeis University, Waltham, Massachusetts
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36
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Goaillard JM, Moubarak E, Tapia M, Tell F. Diversity of Axonal and Dendritic Contributions to Neuronal Output. Front Cell Neurosci 2020; 13:570. [PMID: 32038171 PMCID: PMC6987044 DOI: 10.3389/fncel.2019.00570] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2019] [Accepted: 12/09/2019] [Indexed: 11/13/2022] Open
Abstract
Our general understanding of neuronal function is that dendrites receive information that is transmitted to the axon, where action potentials (APs) are initiated and propagated to eventually trigger neurotransmitter release at synaptic terminals. Even though this canonical division of labor is true for a number of neuronal types in the mammalian brain (including neocortical and hippocampal pyramidal neurons or cerebellar Purkinje neurons), many neuronal types do not comply with this classical polarity scheme. In fact, dendrites can be the site of AP initiation and propagation, and even neurotransmitter release. In several interneuron types, all functions are carried out by dendrites as these neurons are devoid of a canonical axon. In this article, we present a few examples of "misbehaving" neurons (with a non-canonical polarity scheme) to highlight the diversity of solutions that are used by mammalian neurons to transmit information. Moreover, we discuss how the contribution of dendrites and axons to neuronal excitability may impose constraints on the morphology of these compartments in specific functional contexts.
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Affiliation(s)
- Jean-Marc Goaillard
- UMR_S 1072, Aix Marseille Université, INSERM, Faculté de Médecine Secteur Nord, Marseille, France
| | - Estelle Moubarak
- UMR_S 1072, Aix Marseille Université, INSERM, Faculté de Médecine Secteur Nord, Marseille, France
| | - Mónica Tapia
- UMR_S 1072, Aix Marseille Université, INSERM, Faculté de Médecine Secteur Nord, Marseille, France
| | - Fabien Tell
- UMR_S 1072, Aix Marseille Université, INSERM, Faculté de Médecine Secteur Nord, Marseille, France
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37
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Jain A, Narayanan R. Degeneracy in the emergence of spike-triggered average of hippocampal pyramidal neurons. Sci Rep 2020; 10:374. [PMID: 31941985 PMCID: PMC6962224 DOI: 10.1038/s41598-019-57243-8] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2019] [Accepted: 12/26/2019] [Indexed: 12/15/2022] Open
Abstract
Hippocampal pyramidal neurons are endowed with signature excitability characteristics, exhibit theta-frequency selectivity - manifesting as impedance resonance and as a band-pass structure in the spike-triggered average (STA) - and coincidence detection tuned for gamma-frequency inputs. Are there specific constraints on molecular-scale (ion channel) properties in the concomitant emergence of cellular-scale encoding (feature detection and selectivity) and excitability characteristics? Here, we employed a biophysically-constrained unbiased stochastic search strategy involving thousands of conductance-based models, spanning 11 active ion channels, to assess the concomitant emergence of 14 different electrophysiological measurements. Despite the strong biophysical and physiological constraints, we found models that were similar in terms of their spectral selectivity, operating mode along the integrator-coincidence detection continuum and intrinsic excitability characteristics. The parametric combinations that resulted in these functionally similar models were non-unique with weak pair-wise correlations. Employing virtual knockout of individual ion channels in these functionally similar models, we found a many-to-many relationship between channels and physiological characteristics to mediate this degeneracy, and predicted a dominant role for HCN and transient potassium channels in regulating hippocampal neuronal STA. Our analyses reveals the expression of degeneracy, that results from synergistic interactions among disparate channel components, in the concomitant emergence of neuronal excitability and encoding characteristics.
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Affiliation(s)
- Abha Jain
- Cellular Neurophysiology Laboratory, Molecular Biophysics Unit, Indian Institute of Science, Bangalore, India.,Undergraduate program, Indian Institute of Science, Bangalore, India
| | - Rishikesh Narayanan
- Cellular Neurophysiology Laboratory, Molecular Biophysics Unit, Indian Institute of Science, Bangalore, India.
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38
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Basak R, Narayanan R. Robust emergence of sharply tuned place-cell responses in hippocampal neurons with structural and biophysical heterogeneities. Brain Struct Funct 2020; 225:567-590. [PMID: 31900587 DOI: 10.1007/s00429-019-02018-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2019] [Accepted: 12/17/2019] [Indexed: 01/06/2023]
Abstract
Hippocampal pyramidal neurons sustain propagation of fast electrical signals and are electrotonically non-compact structures exhibiting cell-to-cell variability in their complex dendritic arborization. In this study, we demonstrate that sharp place-field tuning and several somatodendritic functional maps concomitantly emerge despite the presence of geometrical heterogeneities in these neurons. We establish this employing an unbiased stochastic search strategy involving thousands of models that spanned several morphologies and distinct profiles of dispersed synaptic localization and channel expression. Mechanistically, employing virtual knockout models (VKMs), we explored the impact of bidirectional modulation in dendritic spike prevalence on place-field tuning sharpness. Consistent with the prior literature, we found that across all morphologies, virtual knockout of either dendritic fast sodium channels or N-methyl-D-aspartate receptors led to a reduction in dendritic spike prevalence, whereas A-type potassium channel knockouts resulted in a non-specific increase in dendritic spike prevalence. However, place-field tuning sharpness was critically impaired in all three sets of VKMs, demonstrating that sharpness in feature tuning is maintained by an intricate balance between mechanisms that promote and those that prevent dendritic spike initiation. From the functional standpoint of the emergence of sharp feature tuning and intrinsic functional maps, within this framework, geometric variability was compensated by a combination of synaptic democracy, the ability of randomly dispersed synapses to yield sharp tuning through dendritic spike initiation, and ion-channel degeneracy. Our results suggest electrotonically non-compact neurons to be endowed with several degrees of freedom, encompassing channel expression, synaptic localization and morphological microstructure, in achieving sharp feature encoding and excitability homeostasis.
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Affiliation(s)
- Reshma Basak
- Cellular Neurophysiology Laboratory, Molecular Biophysics Unit, Indian Institute of Science, Bangalore, 560012, India
| | - Rishikesh Narayanan
- Cellular Neurophysiology Laboratory, Molecular Biophysics Unit, Indian Institute of Science, Bangalore, 560012, India.
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39
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Neuronal population model of globular bushy cells covering unit-to-unit variability. PLoS Comput Biol 2019; 15:e1007563. [PMID: 31881018 PMCID: PMC6934273 DOI: 10.1371/journal.pcbi.1007563] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2019] [Accepted: 11/25/2019] [Indexed: 01/02/2023] Open
Abstract
Computations of acoustic information along the central auditory pathways start in the cochlear nucleus. Bushy cells in the anteroventral cochlear nucleus, which innervate monaural and binaural stations in the superior olivary complex, process and transfer temporal cues relevant for sound localization. These cells are categorized into two groups: spherical and globular bushy cells (SBCs/GBCs). Spontaneous rates of GBCs innervated by multiple auditory nerve (AN) fibers are generally lower than those of SBCs that receive a small number of large AN synapses. In response to low-frequency tonal stimulation, both types of bushy cells show improved phase-locking and entrainment compared to AN fibers. When driven by high-frequency tones, GBCs show primary-like-with-notch or onset-L peristimulus time histograms and relatively irregular spiking. However, previous in vivo physiological studies of bushy cells also found considerable unit-to-unit variability in these response patterns. Here we present a population of models that can simulate the observed variation in GBCs. We used a simple coincidence detection model with an adaptive threshold and systematically varied its six parameters. Out of 567000 parameter combinations tested, 7520 primary-like-with-notch models and 4094 onset-L models were selected that satisfied a set of physiological criteria for a GBC unit. Analyses of the model parameters and output measures revealed that the parameters of the accepted model population are weakly correlated with each other to retain major GBC properties, and that the output spiking patterns of the model are affected by a combination of multiple parameters. Simulations of frequency-dependent temporal properties of the model GBCs showed a reasonable fit to empirical data, supporting the validity of our population modeling. The computational simplicity and efficiency of the model structure makes our approach suitable for future large-scale simulations of binaural information processing that may involve thousands of GBC units. In the auditory system, specialized neuronal circuits process various types of acoustic information. A group of neurons, called globular bushy cells (GBCs), faithfully transfer timing information of acoustic signals to their downstream neurons responsible for the perception of sound location. Previous physiological studies found representative activity patterns of GBCs, but with substantial individual variations among them. In this study, we present a population of models, instead of creating one best model, to account for the observed variations of GBCs. We varied all six parameters of a simple auditory neuron model and selected the combinations of parameters that led to acceptable activity patterns of GBCs. In total, we tested more than half a million combinations and accepted ~11600 GBC models. Temporal spiking patterns of real GBCs depend on the sound frequency, and our model population was able to replicate this trend. The model used here is computationally efficient and can thus serve as a building block for future large-scale simulations of auditory information processing.
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40
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Camacho MB, Vijitbenjaronk WD, Anastasio TJ. Computational Analysis of Therapeutic Neuroadaptation to Chronic Antidepressant in a Model of the Monoaminergic Neurotransmitter and Stress Hormone Systems. Front Pharmacol 2019; 10:1215. [PMID: 31708770 PMCID: PMC6823241 DOI: 10.3389/fphar.2019.01215] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2019] [Accepted: 09/23/2019] [Indexed: 12/28/2022] Open
Abstract
The clinical practice of selective serotonin reuptake inhibitor (SSRI) augmentation relies heavily on trial-and-error. Unfortunately, the drug combinations prescribed today fail to provide relief for many depressed patients. In order to identify potentially more effective treatments, we developed a computational model of the monoaminergic neurotransmitter and stress-steroid systems that neuroadapts to chronic administration of combinations of antidepressant drugs and hormones by adjusting the strengths of its transmitter-system components (TSCs). We used the model to screen 60 chronically administered drug/hormone pairs and triples, and identified as potentially therapeutic those combinations that raised the monoamines (serotonin, norepinephrine, and dopamine) but lowered cortisol following neuroadaptation in the model. We also evaluated the contributions of individual and pairs of TSCs to therapeutic neuroadaptation with chronic SSRI using sensitivity, correlation, and linear temporal-logic analyses. All three approaches revealed that therapeutic neuroadaptation to chronic SSRI is an overdetermined process that depends on multiple TSCs, providing a potential explanation for the clinical finding that no single antidepressant regimen alleviates depressive symptoms in all patients.
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Affiliation(s)
- Mariam B Camacho
- Computational Neurobiology Laboratory, Neuroscience Program, Medical Scholars Program, University of Illinois College of Medicine at Urbana-Champaign, Urbana, IL, United States
| | - Warut D Vijitbenjaronk
- Computational Neurobiology Laboratory, Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL, United States
| | - Thomas J Anastasio
- Computational Neurobiology Laboratory, Department of Molecular and Integrative Physiology, University of Illinois at Urbana-Champaign, Urbana, IL, United States
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Daur N, Zhang Y, Nadim F, Bucher D. Mutual Suppression of Proximal and Distal Axonal Spike Initiation Determines the Output Patterns of a Motor Neuron. Front Cell Neurosci 2019; 13:477. [PMID: 31708748 PMCID: PMC6819512 DOI: 10.3389/fncel.2019.00477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2019] [Accepted: 10/10/2019] [Indexed: 11/13/2022] Open
Abstract
Axonal spike initiation at sites far from somatodendritic integration occurs in a range of systems, but its contribution to neuronal output activity is not well understood. We studied the interactions of distal and proximal spike initiation in an unmyelinated motor axon of the stomatogastric nervous system in the lobster, Homarus americanus. The peripheral axons of the pyloric dilator (PD) neurons generate tonic spiking in response to dopamine application. Centrally generated bursting activity and peripheral spike initiation had mutually suppressive effects. The two PD neurons and the electrically coupled oscillatory anterior burster (AB) neuron form the pacemaker ensemble of the pyloric central pattern generator, and antidromic invasion of central compartments by peripherally generated spikes caused spikelets in AB. Antidromic spikes suppressed burst generation in an activity-dependent manner: slower rhythms were diminished or completely disrupted, while fast rhythmic activity remained robust. Suppression of bursting was based on interference with the underlying slow wave oscillations in AB and PD, rather than a direct effect on spike initiation. A simplified multi-compartment circuit model of the pacemaker ensemble replicated this behavior. Antidromic activity disrupted slow wave oscillations by resetting the inward and outward current trajectories in each spike interval. Centrally generated bursting activity in turn suppressed peripheral spike initiation in an activity-dependent manner. Fast bursting eliminated peripheral spike initiation, while slower bursting allowed peripheral spike initiation to continue during the intervals between bursts. The suppression of peripheral spike initiation was associated with a small after-hyperpolarization in the sub-millivolt range. A realistic model of the PD axon replicated this behavior and showed that a sub-millivolt cumulative after-hyperpolarization across bursts was sufficient to eliminate peripheral spike initiation. This effect was based on the dynamic interaction between slow activity-dependent hyperpolarization caused by the Na+/K+-pump and inward rectification through the hyperpolarization-activated inward current, I h . These results demonstrate that interactions between different spike initiation sites based on spike propagation can shift the relative contributions of different types of activity in an activity-dependent manner. Therefore, distal axonal spike initiation can play an important role in shaping neural output, conditional on the relative level of centrally generated activity.
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Affiliation(s)
- Nelly Daur
- Federated Department of Biological Sciences, New Jersey Institute of Technology and Rutgers University-Newark, Newark, NJ, United States
| | - Yang Zhang
- Department of Mathematical Sciences, New Jersey Institute of Technology, Newark, NJ, United States
| | - Farzan Nadim
- Federated Department of Biological Sciences, New Jersey Institute of Technology and Rutgers University-Newark, Newark, NJ, United States.,Department of Mathematical Sciences, New Jersey Institute of Technology, Newark, NJ, United States
| | - Dirk Bucher
- Federated Department of Biological Sciences, New Jersey Institute of Technology and Rutgers University-Newark, Newark, NJ, United States
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42
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Rathour RK, Narayanan R. Degeneracy in hippocampal physiology and plasticity. Hippocampus 2019; 29:980-1022. [PMID: 31301166 PMCID: PMC6771840 DOI: 10.1002/hipo.23139] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2018] [Revised: 05/27/2019] [Accepted: 06/25/2019] [Indexed: 12/17/2022]
Abstract
Degeneracy, defined as the ability of structurally disparate elements to perform analogous function, has largely been assessed from the perspective of maintaining robustness of physiology or plasticity. How does the framework of degeneracy assimilate into an encoding system where the ability to change is an essential ingredient for storing new incoming information? Could degeneracy maintain the balance between the apparently contradictory goals of the need to change for encoding and the need to resist change towards maintaining homeostasis? In this review, we explore these fundamental questions with the mammalian hippocampus as an example encoding system. We systematically catalog lines of evidence, spanning multiple scales of analysis that point to the expression of degeneracy in hippocampal physiology and plasticity. We assess the potential of degeneracy as a framework to achieve the conjoint goals of encoding and homeostasis without cross-interferences. We postulate that biological complexity, involving interactions among the numerous parameters spanning different scales of analysis, could establish disparate routes towards accomplishing these conjoint goals. These disparate routes then provide several degrees of freedom to the encoding-homeostasis system in accomplishing its tasks in an input- and state-dependent manner. Finally, the expression of degeneracy spanning multiple scales offers an ideal reconciliation to several outstanding controversies, through the recognition that the seemingly contradictory disparate observations are merely alternate routes that the system might recruit towards accomplishment of its goals.
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Affiliation(s)
- Rahul K. Rathour
- Cellular Neurophysiology LaboratoryMolecular Biophysics Unit, Indian Institute of ScienceBangaloreIndia
| | - Rishikesh Narayanan
- Cellular Neurophysiology LaboratoryMolecular Biophysics Unit, Indian Institute of ScienceBangaloreIndia
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43
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Rumbell T, Kozloski J. Dimensions of control for subthreshold oscillations and spontaneous firing in dopamine neurons. PLoS Comput Biol 2019; 15:e1007375. [PMID: 31545787 PMCID: PMC6776370 DOI: 10.1371/journal.pcbi.1007375] [Citation(s) in RCA: 3] [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: 05/02/2019] [Revised: 10/03/2019] [Accepted: 09/04/2019] [Indexed: 11/20/2022] Open
Abstract
Dopaminergic neurons (DAs) of the rodent substantia nigra pars compacta (SNc) display varied electrophysiological properties in vitro. Despite this, projection patterns and functional inputs from DAs to other structures are conserved, so in vivo delivery of consistent, well-timed dopamine modulation to downstream circuits must be coordinated. Here we show robust coordination by linear parameter controllers, discovered through powerful mathematical analyses of data and models, and from which consistent control of DA subthreshold oscillations (STOs) and spontaneous firing emerges. These units of control represent coordinated intracellular variables, sufficient to regulate complex cellular properties with radical simplicity. Using an evolutionary algorithm and dimensionality reduction, we discovered metaparameters, which when regressed against STO features, revealed a 2-dimensional control plane for the neuron’s 22-dimensional parameter space that fully maps the natural range of DA subthreshold electrophysiology. This plane provided a basis for spiking currents to reproduce a large range of the naturally occurring spontaneous firing characteristics of SNc DAs. From it we easily produced a unique population of models, derived using unbiased parameter search, that show good generalization to channel blockade and compensatory intracellular mechanisms. From this population of models, we then discovered low-dimensional controllers for regulating spontaneous firing properties, and gain insight into how currents active in different voltage regimes interact to produce the emergent activity of SNc DAs. Our methods therefore reveal simple regulators of neuronal function lurking in the complexity of combined ion channel dynamics. Electrophysiological activity of the neuronal membrane and concomitant ion channel properties are highly variable within groups of neurons of the same type from the same brain region. Reconciliation of the mechanisms generating neuronal activity is challenging due to the complexity of the interactions between the channel currents involved. Here we present a set of mathematical analyses that uncover the low-dimensional intracellular parameter combinations capable of regulating features of subthreshold oscillations and spontaneous firing in empirically constrained models of nigral dopaminergic neurons. This method generates, from a naive starting point, linear combinations of ion channel properties that are surprisingly capable of reliably controlling a wide variety of emergent electrophysiological activity, thereby predicting drug effects and shedding light on unsuspected compensatory mechanisms that contribute to neuronal function.
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Affiliation(s)
- Timothy Rumbell
- IBM Research, Computational Biology Center, Thomas J. Watson Research Laboratories, Yorktown Heights, New York, United States of America
- * E-mail:
| | - James Kozloski
- IBM Research, Computational Biology Center, Thomas J. Watson Research Laboratories, Yorktown Heights, New York, United States of America
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44
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Golowasch J. Neuromodulation of central pattern generators and its role in the functional recovery of central pattern generator activity. J Neurophysiol 2019; 122:300-315. [PMID: 31066614 DOI: 10.1152/jn.00784.2018] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
Neuromodulators play an important role in how the nervous system organizes activity that results in behavior. Disruption of the normal patterns of neuromodulatory release or production is known to be related to the onset of severe pathologies such as Parkinson's disease, Rett syndrome, Alzheimer's disease, and affective disorders. Some of these pathologies involve neuronal structures that are called central pattern generators (CPGs), which are involved in the production of rhythmic activities throughout the nervous system. Here I discuss the interplay between CPGs and neuromodulatory activity, with particular emphasis on the potential role of neuromodulators in the recovery of disrupted neuronal activity. I refer to invertebrate and vertebrate model systems and some of the lessons we have learned from research on these systems and propose a few avenues for future research. I make one suggestion that may guide future research in the field: neuromodulators restrict the parameter landscape in which CPG components operate, and the removal of neuromodulators may enable a perturbed CPG in finding a new set of parameter values that can allow it to regain normal function.
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Affiliation(s)
- Jorge Golowasch
- Federated Department of Biological Sciences, New Jersey Institute of Technology and Rutgers University-Newark , Newark, New Jersey
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45
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Experimentally-constrained biophysical models of tonic and burst firing modes in thalamocortical neurons. PLoS Comput Biol 2019; 15:e1006753. [PMID: 31095552 PMCID: PMC6541309 DOI: 10.1371/journal.pcbi.1006753] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2018] [Revised: 05/29/2019] [Accepted: 04/10/2019] [Indexed: 01/12/2023] Open
Abstract
Somatosensory thalamocortical (TC) neurons from the ventrobasal (VB) thalamus are central components in the flow of sensory information between the periphery and the cerebral cortex, and participate in the dynamic regulation of thalamocortical states including wakefulness and sleep. This property is reflected at the cellular level by the ability to generate action potentials in two distinct firing modes, called tonic firing and low-threshold bursting. Although the general properties of TC neurons are known, we still lack a detailed characterization of their morphological and electrical properties in the VB thalamus. The aim of this study was to build biophysically-detailed models of VB TC neurons explicitly constrained with experimental data from rats. We recorded the electrical activity of VB neurons (N = 49) and reconstructed morphologies in 3D (N = 50) by applying standardized protocols. After identifying distinct electrical types, we used a multi-objective optimization to fit single neuron electrical models (e-models), which yielded multiple solutions consistent with the experimental data. The models were tested for generalization using electrical stimuli and neuron morphologies not used during fitting. A local sensitivity analysis revealed that the e-models are robust to small parameter changes and that all the parameters were constrained by one or more features. The e-models, when tested in combination with different morphologies, showed that the electrical behavior is substantially preserved when changing dendritic structure and that the e-models were not overfit to a specific morphology. The models and their analysis show that automatic parameter search can be applied to capture complex firing behavior, such as co-existence of tonic firing and low-threshold bursting over a wide range of parameter sets and in combination with different neuron morphologies. Thalamocortical neurons are one of the main components of the thalamocortical system, which is implicated in key functions including sensory transmission and the transition between brain states. These functions are reflected at the cellular level by the ability to generate action potentials in two distinct modes, called burst and tonic firing. Biophysically-detailed computational modeling of these cells can provide a tool to understand the role of these neurons within thalamocortical circuitry. We started by collecting single cell experimental data by applying standardized experimental procedures in brain slices of the rat. Prior work has demonstrated that biological constraints can be integrated using multi-objective optimization to build biologically realistic models of neurons. Here, we employed similar techniques, but extended them to capture the multiple firing modes of thalamic neurons. We compared the model results with additional experimental data, test their generalization and quantitatively reject those that deviated significantly from the experimental variability. These models can be readily integrated in a data-driven pipeline to reconstruct and simulate circuit activity in the thalamocortical system.
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Hartoyo A, Cadusch PJ, Liley DTJ, Hicks DG. Parameter estimation and identifiability in a neural population model for electro-cortical activity. PLoS Comput Biol 2019; 15:e1006694. [PMID: 31145724 PMCID: PMC6542506 DOI: 10.1371/journal.pcbi.1006694] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2018] [Accepted: 04/12/2019] [Indexed: 11/18/2022] Open
Abstract
Electroencephalography (EEG) provides a non-invasive measure of brain electrical activity. Neural population models, where large numbers of interacting neurons are considered collectively as a macroscopic system, have long been used to understand features in EEG signals. By tuning dozens of input parameters describing the excitatory and inhibitory neuron populations, these models can reproduce prominent features of the EEG such as the alpha-rhythm. However, the inverse problem, of directly estimating the parameters from fits to EEG data, remains unsolved. Solving this multi-parameter non-linear fitting problem will potentially provide a real-time method for characterizing average neuronal properties in human subjects. Here we perform unbiased fits of a 22-parameter neural population model to EEG data from 82 individuals, using both particle swarm optimization and Markov chain Monte Carlo sampling. We estimate how much is learned about individual parameters by computing Kullback-Leibler divergences between posterior and prior distributions for each parameter. Results indicate that only a single parameter, that determining the dynamics of inhibitory synaptic activity, is directly identifiable, while other parameters have large, though correlated, uncertainties. We show that the eigenvalues of the Fisher information matrix are roughly uniformly spaced over a log scale, indicating that the model is sloppy, like many of the regulatory network models in systems biology. These eigenvalues indicate that the system can be modeled with a low effective dimensionality, with inhibitory synaptic activity being prominent in driving system behavior.
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Affiliation(s)
- Agus Hartoyo
- Centre for Micro-Photonics, Swinburne University of Technology, Hawthorn, Victoria 3122, Australia
| | - Peter J. Cadusch
- Department of Physics and Astronomy, Swinburne University of Technology, Hawthorn, Victoria 3122, Australia
| | - David T. J. Liley
- Centre for Human Psychopharmacology, School of Health Sciences, Swinburne University of Technology, Hawthorn, Victoria 3122, Australia
- Department of Medicine, University of Melbourne, Parkville, Victoria 3010, Australia
| | - Damien G. Hicks
- Centre for Micro-Photonics, Swinburne University of Technology, Hawthorn, Victoria 3122, Australia
- Department of Physics and Astronomy, Swinburne University of Technology, Hawthorn, Victoria 3122, Australia
- Bioinformatics Division, Walter & Eliza Hall Institute of Medical Research, Parkville, Victoria 3052, Australia
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47
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Slankster E, Odell SR, Mathew D. Strength in diversity: functional diversity among olfactory neurons of the same type. J Bioenerg Biomembr 2019; 51:65-75. [PMID: 30604088 PMCID: PMC6382560 DOI: 10.1007/s10863-018-9779-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2018] [Accepted: 11/13/2018] [Indexed: 01/01/2023]
Abstract
Most animals depend upon olfaction to find food, mates, and to avoid predators. An animal's olfactory circuit helps it sense its olfactory environment and generate critical behavioral responses. The general architecture of the olfactory circuit, which is conserved across species, is made up of a few different neuronal types including first-order receptor neurons, second- and third-order neurons, and local interneurons. Each neuronal type differs in their morphology, physiology, and neurochemistry. However, several recent studies have suggested that there is intrinsic diversity even among neurons of the same type and that this diversity is important for neural function. In this review, we first examine instances of intrinsic diversity observed among individual types of olfactory neurons. Next, we review potential genetic and experience-based plasticity mechanisms that underlie this diversity. Finally, we consider the implications of intrinsic neuronal diversity for circuit function. Overall, we hope to highlight the importance of intrinsic diversity as a previously underestimated property of circuit function.
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Affiliation(s)
- Eryn Slankster
- Department of Biology, University of Nevada, 1664 N. Virginia St., MS: 0314, Reno, NV, 89557, USA
| | - Seth R Odell
- Department of Biology, University of Nevada, 1664 N. Virginia St., MS: 0314, Reno, NV, 89557, USA
- Integrated Neuroscience Program, University of Nevada, Reno, NV, 89557, USA
| | - Dennis Mathew
- Department of Biology, University of Nevada, 1664 N. Virginia St., MS: 0314, Reno, NV, 89557, USA.
- Integrated Neuroscience Program, University of Nevada, Reno, NV, 89557, USA.
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48
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Otsuka S, Omori T. Estimation of neuronal dynamics based on sparse modeling. Neural Netw 2018; 109:137-146. [PMID: 30453159 DOI: 10.1016/j.neunet.2018.10.006] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2018] [Revised: 07/13/2018] [Accepted: 10/09/2018] [Indexed: 10/28/2022]
Abstract
Elucidating neural dynamics is one of the important subjects in neuroscience. To elucidate nonlinear dynamics of single neurons, it is important to extract nonlinear membrane currents from many types of membrane current candidates. In this study, we propose a sparse modeling method for estimating a conductance-based neuron model from observed data, by extracting necessary membrane currents from multiple candidates. We show using simulated data that our proposed sparse modeling approach with different sparsity levels for distinct membrane currents extracts only necessary membrane currents from candidates more accurately, compared with least-squares method and sparse method with uniform sparsity level.
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Affiliation(s)
- Shinya Otsuka
- Department of Electrical and Electronic Engineering, Graduate School of Engineering, Kobe University, Japan
| | - Toshiaki Omori
- Department of Electrical and Electronic Engineering, Graduate School of Engineering, Kobe University, Japan.
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49
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Migliore R, Lupascu CA, Bologna LL, Romani A, Courcol JD, Antonel S, Van Geit WAH, Thomson AM, Mercer A, Lange S, Falck J, Rössert CA, Shi Y, Hagens O, Pezzoli M, Freund TF, Kali S, Muller EB, Schürmann F, Markram H, Migliore M. The physiological variability of channel density in hippocampal CA1 pyramidal cells and interneurons explored using a unified data-driven modeling workflow. PLoS Comput Biol 2018; 14:e1006423. [PMID: 30222740 PMCID: PMC6160220 DOI: 10.1371/journal.pcbi.1006423] [Citation(s) in RCA: 63] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2018] [Revised: 09/27/2018] [Accepted: 08/08/2018] [Indexed: 11/19/2022] Open
Abstract
Every neuron is part of a network, exerting its function by transforming multiple spatiotemporal synaptic input patterns into a single spiking output. This function is specified by the particular shape and passive electrical properties of the neuronal membrane, and the composition and spatial distribution of ion channels across its processes. For a variety of physiological or pathological reasons, the intrinsic input/output function may change during a neuron's lifetime. This process results in high variability in the peak specific conductance of ion channels in individual neurons. The mechanisms responsible for this variability are not well understood, although there are clear indications from experiments and modeling that degeneracy and correlation among multiple channels may be involved. Here, we studied this issue in biophysical models of hippocampal CA1 pyramidal neurons and interneurons. Using a unified data-driven simulation workflow and starting from a set of experimental recordings and morphological reconstructions obtained from rats, we built and analyzed several ensembles of morphologically and biophysically accurate single cell models with intrinsic electrophysiological properties consistent with experimental findings. The results suggest that the set of conductances expressed in any given hippocampal neuron may be considered as belonging to two groups: one subset is responsible for the major characteristics of the firing behavior in each population and the other is responsible for a robust degeneracy. Analysis of the model neurons suggests several experimentally testable predictions related to the combination and relative proportion of the different conductances that should be expressed on the membrane of different types of neurons for them to fulfill their role in the hippocampus circuitry.
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Affiliation(s)
- Rosanna Migliore
- Institute of Biophysics, National Research Council, Palermo, Italy
| | | | - Luca L. Bologna
- Institute of Biophysics, National Research Council, Palermo, Italy
| | - Armando Romani
- Blue Brain Project, École Polytechnique Fédérale de Lausanne, Campus Biotech, Geneva, Switzerland
| | - Jean-Denis Courcol
- Blue Brain Project, École Polytechnique Fédérale de Lausanne, Campus Biotech, Geneva, Switzerland
| | - Stefano Antonel
- Blue Brain Project, École Polytechnique Fédérale de Lausanne, Campus Biotech, Geneva, Switzerland
| | - Werner A. H. Van Geit
- Blue Brain Project, École Polytechnique Fédérale de Lausanne, Campus Biotech, Geneva, Switzerland
| | | | | | - Sigrun Lange
- University College London, London, United Kingdom
- University of Westminster, London, United Kingdom
| | - Joanne Falck
- University College London, London, United Kingdom
| | - Christian A. Rössert
- Blue Brain Project, École Polytechnique Fédérale de Lausanne, Campus Biotech, Geneva, Switzerland
| | - Ying Shi
- Blue Brain Project, École Polytechnique Fédérale de Lausanne, Campus Biotech, Geneva, Switzerland
| | - Olivier Hagens
- Laboratory of Neural Microcircuitry (LNMC), Brain Mind Institute, EPFL, Lausanne, Switzerland
| | - Maurizio Pezzoli
- Laboratory of Neural Microcircuitry (LNMC), Brain Mind Institute, EPFL, Lausanne, Switzerland
| | - Tamas F. Freund
- Institute of Experimental Medicine, Hungarian Academy of Sciences, Budapest, Hungary
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
| | - Szabolcs Kali
- Institute of Experimental Medicine, Hungarian Academy of Sciences, Budapest, Hungary
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
| | - Eilif B. Muller
- Blue Brain Project, École Polytechnique Fédérale de Lausanne, Campus Biotech, Geneva, Switzerland
| | - Felix Schürmann
- Blue Brain Project, École Polytechnique Fédérale de Lausanne, Campus Biotech, Geneva, Switzerland
| | - Henry Markram
- Blue Brain Project, École Polytechnique Fédérale de Lausanne, Campus Biotech, Geneva, Switzerland
| | - Michele Migliore
- Institute of Biophysics, National Research Council, Palermo, Italy
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50
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Basak R, Narayanan R. Spatially dispersed synapses yield sharply-tuned place cell responses through dendritic spike initiation. J Physiol 2018; 596:4173-4205. [PMID: 29893405 PMCID: PMC6117611 DOI: 10.1113/jp275310] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2018] [Accepted: 06/01/2018] [Indexed: 12/24/2022] Open
Abstract
KEY POINTS The generation of dendritic spikes and the consequent sharp tuning of neuronal responses are together attainable even when iso-feature synapses are randomly dispersed across the dendritic arbor. Disparate combinations of channel conductances with distinct configurations of randomly dispersed place field synapses concomitantly yield similar sharp tuning profiles and similar functional maps of several intrinsic properties. Targeted synaptic plasticity converts silent cells to place cells for specific place fields in models with disparate channel combinations that receive dispersed synaptic inputs from multiple place field locations. Dispersed localization of iso-feature synapses is a strong candidate for achieving sharp feature selectivity in neurons across sensory-perceptual systems, with several degrees of freedom in relation to synaptic locations. Quantitative evidence for the possibility that degeneracy (i.e. the ability of disparate structural components to yield similar functional outcomes) could act as a broad framework that effectively accomplishes the twin goals of input-feature encoding and homeostasis of intrinsic properties without cross interferences. ABSTRACT A prominent hypothesis spanning several sensory-perceptual systems implicates spatially clustered synapses in the generation of dendritic spikes that mediate sharply-tuned neuronal responses to input features. In this conductance-based morphologically-precise computational study, we tested this hypothesis by systematically analysing the impact of distinct synaptic and channel localization profiles on sharpness of spatial tuning in hippocampal pyramidal neurons. We found that the generation of dendritic spikes, the emergence of an excitatory ramp in somatic voltage responses, the expression of several intrinsic somatodendritic functional maps and sharp tuning of place-cell responses were all attainable even when iso-feature synapses are randomly dispersed across the dendritic arbor of models with disparate channel combinations. Strikingly, the generation and propagation of dendritic spikes, reliant on dendritic sodium channels and N-methyl-d-asparate receptors, mediated the sharpness of spatial tuning achieved with dispersed synaptic localization. To ensure that our results were not artefacts of narrow parametric choices, we confirmed these conclusions with independent multiparametric stochastic search algorithms spanning thousands of unique models for each synaptic localization scenario. Next, employing virtual knockout models, we demonstrated a vital role for dendritically expressed voltage-gated ion channels, especially the transient potassium channels, in maintaining sharpness of place-cell tuning. Importantly, we established that synaptic potentiation targeted to afferents from one specific place field was sufficient to impart place field selectivity even when intrinsically disparate neurons received randomly dispersed afferents from multiple place field locations. Our results provide quantitative evidence for disparate combinations of channel and synaptic localization profiles to concomitantly yield similar tuning and similar intrinsic properties.
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Affiliation(s)
- Reshma Basak
- Cellular Neurophysiology LaboratoryMolecular Biophysics UnitIndian Institute of ScienceBangaloreIndia
| | - Rishikesh Narayanan
- Cellular Neurophysiology LaboratoryMolecular Biophysics UnitIndian Institute of ScienceBangaloreIndia
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