Differential and History-Dependent Modulation of a Stretch Receptor in the Stomatogastric System of the Crab,<i>Cancer borealis</i>

Birmingham, John T.; Billimoria, Cyrus P.; DeKlotz, Timothy; Stewart, Raj A.; Marder, Eve

doi:10.1152/jn.00397.2003

Cited by 30 publications

(46 citation statements)

References 50 publications

(41 reference statements)

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“…Responses of individual neurons, synapses, and circuits to neuromodulation are often quite variable (50,51). In some instances, it is clear that the effect of the modulator depends on some obvious feature of the state of the preparation (52)(53)(54)(55)(56). In some instances, this variability arises from unknown sources and is likely a consequence of differing underlying cell or circuit parameters.…”

Section: Parameter Compensation and Correlationsmentioning

confidence: 99%

Variability, compensation, and modulation in neurons and circuits

Marder

2011

Proc. Natl. Acad. Sci. U.S.A.

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I summarize recent computational and experimental work that addresses the inherent variability in the synaptic and intrinsic conductances in normal healthy brains and shows that multiple solutions (sets of parameters) can produce similar circuit performance. I then discuss a number of issues raised by this observation, such as which parameter variations arise from compensatory mechanisms and which reflect insensitivity to those particular parameters. I ask whether networks with different sets of underlying parameters can nonetheless respond reliably to neuromodulation and other global perturbations. At the computational level, I describe a paradigm shift in which it is becoming increasingly common to develop families of models that reflect the variance in the biological data that the models are intended to illuminate rather than single, highly tuned models. On the experimental side, I discuss the inherent limitations of overreliance on mean data and suggest that it is important to look for compensations and correlations among as many system parameters as possible, and between each system parameter and circuit performance. This second paradigm shift will require moving away from measurements of each system component in isolation but should reveal important previously undescribed principles in the organization of complex systems such as brains.circuit dynamics | neuronal variability | neuronal homeostasis | dynamic clamp A ll experimental biologists face a daily conundrum: on the one hand, we know that all individual biological organisms, be they lobsters, cats, or humans, are distinct individuals. On the other hand, we must do experiments on multiple individuals to ensure the reliability of our results. As biologists wishing to understand how the function of a cell, a circuit, or a brain depends on the properties of its constituent processes, we confront two issues: (i) all our data come with associated measurement error (often difficult to assess), and (ii) there is considerable natural variability in the populations we study. Consequently, we conventionally rely on statistics calculated from populations to assure ourselves that our measurements are reliable. Most commonly, we report mean data, with the underlying assumption that these means capture something akin to a "platonic ideal" of the individual neurons or animals whose properties were measured. Although this strategy has been enormously useful over the years, it has many limitations, some of which I discuss below. Multiple Solutions and Failure of AveragingDespite the widespread use of means, computational work has shown unambiguously some of the dangers and confounds that can come from exclusive reliance on mean data (1-3). One example of this comes from a study in which several thousand model neurons were generated by randomly picking the maximal conductances of the five different ionic conductances in the model (2). Fig. 1 shows three examples of single-spike bursters chosen from a population of 164 single-spike bursters generated in this study. Alth...

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Section: Parameter Compensation and Correlationsmentioning

confidence: 99%

Variability, compensation, and modulation in neurons and circuits

Marder

2011

Proc. Natl. Acad. Sci. U.S.A.

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337

367

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“…Another level of control in this system is suggested by the fact that the sensitivity of GPR to muscle stretch is itself modulated (Birmingham, 2001;Birmingham et al, 2003). We therefore anticipate that our appreciation for how sensory signals regulate neural circuit activity will be extended further as we assess the consequences resulting from modulation of GPR sensitivity for its influence on the gastric mill motor circuit.…”

Section: Presynaptic Inhibition Enables Sensory Signals To Dynamicallmentioning

confidence: 99%

Proprioceptor Regulation of Motor Circuit Activity by Presynaptic Inhibition of a Modulatory Projection Neuron

Beenhakker¹,

DeLong²,

Saideman³

et al. 2005

J. Neurosci.

118

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Phasically active sensory systems commonly influence rhythmic motor activity via synaptic actions on the relevant circuit and/or motor neurons. Using the crab stomatogastric nervous system (STNS), we identified a distinct synaptic action by which an identified proprioceptor, the gastropyloricmusclestretchreceptor(GPR)neuron,regulatesthegastricmill(chewing)motorrhythm.Previousworkshowedthatrhythmically stimulating GPR in a gastric mill-like pattern, in the isolated STNS, elicits the gastric mill rhythm via its activation of two identified projection neurons, modulatory commissural neuron 1 (MCN1) and commissural projection neuron 2, in the commissural ganglia. Here, we determine how activation of GPR with a behaviorally appropriate pattern (active during each gastric mill retractor phase) influences an ongoing gastric mill rhythm via actions in the stomatogastric ganglion, where the gastric mill circuit is located. Stimulating GPR during each retractor phase selectively prolongs that phase and thereby slows the ongoing rhythm. This selective action on the retractor phase results from two distinct GPR actions. First, GPR presynaptically inhibits the axon terminals of MCN1, reducing MCN1 excitation of all gastric mill neurons. Second, GPR directly excites the retractor phase neurons. Because MCN1 transmitter release occurs during each retractor phase, these parallel GPR actions selectively reduce the buildup of excitatory drive to the protractor phase neurons, delaying each protractor burst. Thus, rhythmic proprioceptor feedback to a motor circuit can result from a global reduction in excitatory drive to that circuit, via presynaptic inhibition, coupled with a phase-specific excitatory input that prolongs the excited phase by delaying the onset of the subsequent phase.

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“…cockroaches, crickets and termites (Stay and Tobe, 2007). A-type peptides have also been found in a number of crustaceans (Duve et al, 1997;Dircksen et al, 1999;Duve et al, 2002;Huybrechts et al, 2003;Fu et al, 2005;Yasuda-Kamatani and Yasuda, 2006;Yin et al, 2006;Christie et al, 2008a;Ma et al, 2008;Gard et al, 2009;Ma et al, 2009), where they have been shown to function as locally released and/or hormonally delivered neuro/myomodulators (Skiebe and Schneider, 1994;Jorge-Rivera and Marder, 1997;Jorge-Rivera et al, 1998;Dircksen et al, 1999;Kreissl et al, 1999;Birmingham et al, 2003;Billimoria et al, 2006;Cruz-Bermúdez and Marder, 2007). Molecular, biochemical and mass spectral analyses have shown that multiple isoforms of A-type peptides are common in both insect and crustacean species, with multiple peptides encoded by the known arthropod A-AST prepro-hormones (e.g.…”

Section: Introductionmentioning

confidence: 99%

Identification of SYWKQCAFNAVSCFamide: a broadly conserved crustacean C-type allatostatin-like peptide with both neuromodulatory and cardioactive properties

Dickinson

Wiwatpanit

Gabranski

et al. 2009

Journal of Experimental Biology

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SUMMARYThe allatostatins comprise three structurally distinct peptide families that regulate juvenile hormone production by the insect corpora allata. A-type family members contain the C-terminal motif -YXFGLamide and have been found in species from numerous arthropod taxa. Members of the B-type family exhibit a -WX 6 Wamide C-terminus and, like the A-type peptides, appear to be broadly conserved within the Arthropoda. By contrast, members of the C-type family, typified by the unblocked C-terminus -PISCF, a pyroglutamine blocked N-terminus, and a disulfide bridge between two internal Cys residues, have only been found in holometabolous insects, i.e. lepidopterans and dipterans. Here, using transcriptomics, we have identified SYWKQCAFNAVSCFamide (disulfide bridging predicted between the two Cys residues), a known honeybee and water flea C-typelike peptide, from the American lobster Homarus americanus (infraorder Astacidea). Using matrix assisted laser desorption/ionization Fourier transform mass spectrometry (MALDI-FTMS), a mass corresponding to that of SYWKQCAFNAVSCFamide was detected in the H. americanus brain, supporting the existence of this peptide and its theorized structure. Furthermore, SYWKQCAFNAVSCFamide was detected by MALDI-FTMS in neural tissues from five additional astacideans as well as 19 members of four other decapod infraorders (i.e. Achelata, Anomura, Brachyura and Thalassinidea), suggesting that it is a broadly conserved decapod peptide. In H. americanus, SYWKQCAFNAVSCFamide is capable of modulating the output of both the pyloric circuit of the stomatogastric nervous system and the heart. This is the first demonstration of bioactivity for this peptide in any species.

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Differential and History-Dependent Modulation of a Stretch Receptor in the Stomatogastric System of the Crab,Cancer borealis

Cited by 30 publications

References 50 publications

Variability, compensation, and modulation in neurons and circuits

Variability, compensation, and modulation in neurons and circuits

Proprioceptor Regulation of Motor Circuit Activity by Presynaptic Inhibition of a Modulatory Projection Neuron

Identification of SYWKQCAFNAVSCFamide: a broadly conserved crustacean C-type allatostatin-like peptide with both neuromodulatory and cardioactive properties

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