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      Checks and Balances in Neuromodulation

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          Abstract

          Neuromodulators such as monoamines and peptides play important roles in activating and reconfiguring neural networks to allow behavioral flexibility. While the net effects of a neuromodulator change the network in a particular direction, careful studies of modulatory effects reveal multiple cases where a neuromodulator will activate functionally opposing mechanisms on a single neuron or synapse. This review gives examples of such opposing actions, focusing on the lobster pyloric network, and discusses their possible functional significance. One important action of opposing modulatory actions may be to stabilize the modulated state of the network, and to prevent it from being overmodulated and becoming non-functional.

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          Most cited references31

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          The self-tuning neuron: synaptic scaling of excitatory synapses.

          Homeostatic synaptic scaling is a form of synaptic plasticity that adjusts the strength of all of a neuron's excitatory synapses up or down to stabilize firing. Current evidence suggests that neurons detect changes in their own firing rates through a set of calcium-dependent sensors that then regulate receptor trafficking to increase or decrease the accumulation of glutamate receptors at synaptic sites. Additional mechanisms may allow local or network-wide changes in activity to be sensed through parallel pathways, generating a nested set of homeostatic mechanisms that operate over different temporal and spatial scales.
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            Quantitative expression profiling of identified neurons reveals cell-specific constraints on highly variable levels of gene expression.

            The postdevelopmental basis of cellular identity and the unique cellular output of a particular neuron type are of particular interest in the nervous system because a detailed understanding of circuits responsible for complex processes in the brain is impeded by the often ambiguous classification of neurons in these circuits. Neurons have been classified by morphological, electrophysiological, and neurochemical techniques. More recently, molecular approaches, particularly microarray, have been applied to the question of neuronal identity. With the realization that proteins expressed exclusively in only one type of neuron are rare, expression profiles obtained from neuronal subtypes are analyzed to search for diagnostic patterns of gene expression. However, this expression profiling hinges on one critical and implicit assumption: that neurons of the same type in different animals achieve their conserved functional output via conserved levels and quantitative relationships of gene expression. Here we exploit the unambiguously identifiable neurons in the crab stomatogastric ganglion to investigate the precise quantitative expression profiling of neurons at the level of single-cell ion channel expression. By measuring absolute mRNA levels of six different channels in the same individually identified neurons, we demonstrate that not only do individual cell types possess highly variable levels of channel expression but that this variability is constrained by unique patterns of correlated channel expression.
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              Activity-independent homeostasis in rhythmically active neurons.

              The shal gene encodes the transient potassium current (I(A)) in neurons of the lobster stomatogastric ganglion. Overexpression of Shal by RNA injection into neurons produces a large increase in I(A), but surprisingly little change in the neuron's firing properties. Accompanying the increase in I(A) is a dramatic and linearly correlated increase in the hyperpolarization-activated inward current (I(h)). The enhanced I(h) electrophysiologically compensates for the enhanced I(A), since pharmacological blockade of I(h) uncovers the physiological effects of the increased I(A). Expression of a nonfunctional mutant Shal also induces a large increase in I(h), demonstrating a novel activity-independent coupling between the Shal protein and I(h) enhancement. Since I(A) and I(h) influence neuronal activity in opposite directions, our results suggest a selective coregulation of these channels as a mechanism for constraining cell activity within appropriate physiological parameters.
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                Author and article information

                Journal
                Front Behav Neurosci
                Front. Behav. Neurosci.
                Frontiers in Behavioral Neuroscience
                Frontiers Research Foundation
                1662-5153
                11 June 2010
                21 July 2010
                2010
                : 4
                : 47
                Affiliations
                [1] 1simpleDepartment of Neurobiology and Behavior, Cornell University Ithaca, NY, USA
                Author notes

                Edited by: Kathleen A. French, University of California San Diego, USA

                Reviewed by: David Schulz, University of Missouri-Columbia, USA

                *Correspondence: Ronald M. Harris-Warrick, Department of Neurobiology and Behavior, Seeley G. Mudd Hall, Cornell University, Ithaca, NY 14853, USA. e-mail: rmh4@ 123456cornell.edu
                Article
                10.3389/fnbeh.2010.00047
                2917248
                20700503
                892671e7-912d-4335-a4d8-899b0e879d4c
                Copyright © 2010 Harris-Warrick and Johnson.

                This is an open-access article subject to an exclusive license agreement between the authors and the Frontiers Research Foundation, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are credited.

                History
                : 14 April 2010
                : 02 July 2010
                Page count
                Figures: 6, Tables: 0, Equations: 0, References: 36, Pages: 9, Words: 6390
                Categories
                Neuroscience
                Review Article

                Neurosciences
                neuromodulation,network,synapse,ion channel,opposition,central pattern generator
                Neurosciences
                neuromodulation, network, synapse, ion channel, opposition, central pattern generator

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