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      Chloride dynamics alter the input-output properties of neurons

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          Abstract

          Fast synaptic inhibition is a critical determinant of neuronal output, with subcellular targeting of synaptic inhibition able to exert different transformations of the neuronal input-output function. At the receptor level, synaptic inhibition is primarily mediated by chloride-permeable Type A GABA receptors. Consequently, dynamics in the neuronal chloride concentration can alter the functional properties of inhibitory synapses. How differences in the spatial targeting of inhibitory synapses interact with intracellular chloride dynamics to modulate the input-output function of neurons is not well understood. To address this, we developed computational models of multi-compartment neurons that incorporate experimentally parametrised mechanisms to account for neuronal chloride influx, diffusion, and extrusion. We found that synaptic input (either excitatory, inhibitory, or both) can lead to subcellular variations in chloride concentration, despite a uniform distribution of chloride extrusion mechanisms. Accounting for chloride changes resulted in substantial alterations in the neuronal input-output function. This was particularly the case for peripherally targeted dendritic inhibition where dynamic chloride compromised the ability of inhibition to offset neuronal input-output curves. Our simulations revealed that progressive changes in chloride concentration mean that the neuronal input-output function is not static but varies significantly as a function of the duration of synaptic drive. Finally, we found that the observed effects of dynamic chloride on neuronal output were mediated by changes in the dendritic reversal potential for GABA. Our findings provide a framework for understanding the computational effects of chloride dynamics on dendritically targeted synaptic inhibition.

          Author summary

          The fundamental unit of computation in the brain is the neuron, whose output reflects information within the brain. A determining factor in the transfer and processing of information in the brain is the modulation of activity by inhibitory synaptic inputs. Fast synaptic inhibition is mediated by the neurotransmitter GABA binding to GABA A receptors, which are permeable to chloride ions. How changes in chloride ion concentration affect neuronal output is an important consideration for information flow in the brain that is currently not being thoroughly investigated. In this research, we used multi-compartmental models of neurons to link the deleterious effects that accumulation of chloride ions can have on inhibitory signalling with changes in neuronal ouput. Together, our results highlight the importance of accounting for changes in chloride concentration in theoretical and computer-based models that seek to explore the computational properties of inhibition.

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          Most cited references55

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          A simple method for organotypic cultures of nervous tissue.

          Hippocampal slices prepared from 2-23-day-old neonates were maintained in culture at the interface between air and a culture medium. They were placed on a sterile, transparent and porous membrane and kept in petri dishes in an incubator. No plasma clot or roller drum were used. This method yields thin slices which remain 1-4 cell layers thick and are characterized by a well preserved organotypic organization. Pyramidal neurons labelled by extra- and intracellular application of horse radish peroxidase resemble by the organization and complexity of their dendritic processes those observed in situ at a comparable developmental stage. Excitatory and inhibitory synaptic potentials can easily be analysed using extra- or intracellular recording techniques. After a few days in culture, long-term potentiation of synaptic responses can reproducibly be induced. Evidence for a sprouting response during the first days in culture or following sections is illustrated. This technique may represent an interesting alternative to roller tube cultures for studies of the developmental changes occurring during the first days or weeks in culture.
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            Parvalbumin-Expressing Interneurons Linearly Transform Cortical Responses to Visual Stimuli

            The response of cortical neurons to a sensory stimulus is shaped by the network in which they are embedded. Here we establish a role of parvalbumin (PV)-expressing cells, a large class of inhibitory neurons that target the soma and perisomatic compartments of pyramidal cells, in controlling cortical responses. By bidirectionally manipulating PV cell activity in visual cortex we show that these neurons strongly modulate layer 2/3 pyramidal cell spiking responses to visual stimuli while only modestly affecting their tuning properties. PV cells' impact on pyramidal cells is captured by a linear transformation, both additive and multiplicative, with a threshold. These results indicate that PV cells are ideally suited to modulate cortical gain and establish a causal relationship between a select neuron type and specific computations performed by the cortex during sensory processing. Copyright © 2012 Elsevier Inc. All rights reserved.
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              Division and subtraction by distinct cortical inhibitory networks in vivo.

              Brain circuits process information through specialized neuronal subclasses interacting within a network. Revealing their interplay requires activating specific cells while monitoring others in a functioning circuit. Here we use a new platform for two-way light-based circuit interrogation in visual cortex in vivo to show the computational implications of modulating different subclasses of inhibitory neurons during sensory processing. We find that soma-targeting, parvalbumin-expressing (PV) neurons principally divide responses but preserve stimulus selectivity, whereas dendrite-targeting, somatostatin-expressing (SOM) neurons principally subtract from excitatory responses and sharpen selectivity. Visualized in vivo cell-attached recordings show that division by PV neurons alters response gain, whereas subtraction by SOM neurons shifts response levels. Finally, stimulating identified neurons while scanning many target cells reveals that single PV and SOM neurons functionally impact only specific subsets of neurons in their projection fields. These findings provide direct evidence that inhibitory neuronal subclasses have distinct and complementary roles in cortical computations.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SoftwareRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: MethodologyRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: SupervisionRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS Comput Biol
                PLoS Comput. Biol
                plos
                ploscomp
                PLoS Computational Biology
                Public Library of Science (San Francisco, CA USA )
                1553-734X
                1553-7358
                26 May 2020
                May 2020
                : 16
                : 5
                : e1007932
                Affiliations
                [1 ] Division of Cell Biology, Department of Human Biology, Neuroscience Institute and Institute of Infectious Disease and Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
                [2 ] Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, United Kingdom
                [3 ] Department of Pharmacology, University of Oxford, Oxford, United Kingdom
                Inria, FRANCE
                Author notes

                The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0002-4809-5059
                http://orcid.org/0000-0001-9307-4241
                Article
                PCOMPBIOL-D-19-01233
                10.1371/journal.pcbi.1007932
                7307785
                32453795
                97291797-2e1a-423d-8ce9-345431803081
                © 2020 Currin et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 24 July 2019
                : 6 May 2020
                Page count
                Figures: 6, Tables: 2, Pages: 22
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100000268, Biotechnology and Biological Sciences Research Council;
                Award ID: BB/P019854/1
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100000781, European Research Council;
                Award ID: 617670
                Award Recipient :
                Funded by: Future Leaders – African Independent Research
                Award ID: FLR\R1\190829
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100000265, Medical Research Council;
                Award ID: MR/R005427/1
                Award Recipient :
                CBC is supported by the German Deutscher Akademischer Austauschdienst (DAAD, https://www.daad.de/), the South African (SA) National Research Foundation (NRF, https://www.nrf.ac.za), and the University of Cape Town (UCT, https://www.uct.ac.za). AJT is supported by a grant from the Biotechnology and Biological Sciences Research Council (BBSRC, https://bbsrc.ukri.org) (BB/P019854/1) and the (MRC, https://mrc.ukri.org/) (MR/R005427/1). Some of the research leading to these results has received funding from European Research Council (ERC, https://erc.europa.eu) grant agreement number 617670 to CJA. JVR has received funding support from the Blue Brain Project ( https://www.epfl.ch/research/domains/bluebrain/), the SA NRF, SA Medical Research Council (MRC, http://www.mrc.ac.za), Wellcome Trust ( https://wellcome.ac.uk) and the Future Leaders – African Independent Research (FLAIR, https://royalsociety.org/grants-schemes-awards/grants/flair/) Fellowship Programme (FLR\R1\190829): a partnership between the African Academy of Sciences and the Royal Society funded by the UK Government’s Global Challenges Research Fund. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Cell Biology
                Cellular Types
                Animal Cells
                Neurons
                Neuronal Dendrites
                Biology and Life Sciences
                Neuroscience
                Cellular Neuroscience
                Neurons
                Neuronal Dendrites
                Biology and Life Sciences
                Anatomy
                Nervous System
                Synapses
                Medicine and Health Sciences
                Anatomy
                Nervous System
                Synapses
                Biology and Life Sciences
                Physiology
                Electrophysiology
                Neurophysiology
                Synapses
                Medicine and Health Sciences
                Physiology
                Electrophysiology
                Neurophysiology
                Synapses
                Biology and Life Sciences
                Neuroscience
                Neurophysiology
                Synapses
                Physical Sciences
                Chemistry
                Chemical Compounds
                Chlorides
                Biology and Life Sciences
                Cell Biology
                Cellular Types
                Animal Cells
                Neurons
                Biology and Life Sciences
                Neuroscience
                Cellular Neuroscience
                Neurons
                Research and Analysis Methods
                Simulation and Modeling
                Biology and Life Sciences
                Cell Biology
                Cell Processes
                Cellular Extrusion
                Biology and Life Sciences
                Physiology
                Electrophysiology
                Membrane Potential
                Medicine and Health Sciences
                Physiology
                Electrophysiology
                Membrane Potential
                Biology and Life Sciences
                Physiology
                Electrophysiology
                Membrane Potential
                Action Potentials
                Medicine and Health Sciences
                Physiology
                Electrophysiology
                Membrane Potential
                Action Potentials
                Biology and Life Sciences
                Physiology
                Electrophysiology
                Neurophysiology
                Action Potentials
                Medicine and Health Sciences
                Physiology
                Electrophysiology
                Neurophysiology
                Action Potentials
                Biology and Life Sciences
                Neuroscience
                Neurophysiology
                Action Potentials
                Custom metadata
                vor-update-to-uncorrected-proof
                2020-06-22
                All the experimental data presented in this manuscript has been made publicly available and may be accessed using the following link: http://raimondolab.com/2020/05/07/chloride-dynamics-data/. All the code to generate the modelling data has been made publicly available and may be accessed using the following link: https://github.com/ChrisCurrin/chloride-dynamics-io-neuron.

                Quantitative & Systems biology
                Quantitative & Systems biology

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