Models Wagging the Dog: Are Circuits Constructed with Disparate Parameters?

Nowotny, Thomas; Szűcs, Attila; Levi, Rafael; Selverston, Allen I.

doi:10.1162/neco.2007.19.8.1985

Cited by 34 publications

(38 citation statements)

References 29 publications

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“…Can Circuits with Different Underlying Structures Respond Reliably to Perturbation? There must be perturbations that will differentiate among circuits with different sets of underlying parameters even if they produce similar behaviors (46). Therefore, it is interesting to ask how reliably different individual animals respond to the kinds of perturbations that they routinely see in their lifetimes.…”

Section: Parameter Compensation and Correlationsmentioning

confidence: 99%

Variability, compensation, and modulation in neurons and circuits

Marder

2011

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

337

370

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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.

337

370

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“…Both modeling and experimental studies demonstrate that similar circuit function can result from a large variation in the synaptic and intrinsic conductances that contribute to circuit function (1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11). This finding suggests that each individual could, during development, build a brain that differs significantly from all others and poses the question of whether circuits with diverse underlying structure, yet similar behavior, can respond reliably (12,13) to neuromodulatory substances that alter brain states (14)(15)(16)(17)(18)(19)(20)(21). Therefore, we used the dynamic clamp (22,23) to construct 2-cell circuits (24) from neurons of the crab stomatogastric ganglion (STG).…”

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confidence: 99%

Reliable neuromodulation from circuits with variable underlying structure

Grashow

Brookings

Marder

2009

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

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Recent work argues that similar network performance can result from highly variable sets of network parameters, raising the question of whether neuromodulation can be reliable across individuals with networks with different sets of synaptic strengths and intrinsic membrane conductances. To address this question, we used the dynamic clamp to construct 2-cell reciprocally inhibitory networks from gastric mill (GM) neurons of the crab stomatogastric ganglion. When the strength of the artificial inhibitory synapses (gsyn) and the conductance of an artificial Ih (gh) were varied with the dynamic clamp, a variety of network behaviors resulted, including regions of stable alternating bursting. Maps of network output as a function of gsyn and gh were constructed in normal saline and again in the presence of serotonin or oxotremorine. Both serotonin and oxotremorine depolarize and excite isolated individual GM neurons, but by different cellular mechanisms. Serotonin and oxotremorine each increased the size of the parameter regions that supported alternating bursting, and, on average, increased burst frequency. Nonetheless, in both cases some parameter sets within the sample space deviated from the mean population response and decreased in frequency. These data provide insight into why pharmacological treatments that work in most individuals can generate anomalous actions in a few individuals, and they have implications for understanding the evolution of nervous systems. dynamic clamp ͉ evolution ͉ serotonin ͉ stomatogastric ganglion ͉ oscillator H ow different are the brains in a population of healthy individuals of the same species? Both modeling and experimental studies demonstrate that similar circuit function can result from a large variation in the synaptic and intrinsic conductances that contribute to circuit function (1-11). This finding suggests that each individual could, during development, build a brain that differs significantly from all others and poses the question of whether circuits with diverse underlying structure, yet similar behavior, can respond reliably (12, 13) to neuromodulatory substances that alter brain states (14-21). Therefore, we used the dynamic clamp (22, 23) to construct 2-cell circuits (24) from neurons of the crab stomatogastric ganglion (STG). The strength of the reciprocal inhibitory synapses (g syn ) and the conductance of an artificial I h (g h ) were varied (24), and the resulting activity patterns were recorded in control saline and in response to 2 neuromodulatory substances, serotonin and the muscarinic agonist, oxotremorine.In these hybrid experiments, the intrinsic properties of these 2 biological neurons vary between each other and across preparations while 2 of the important parameters for network performance are under experimental control. This method ensures that the variability intrinsic to biological systems is retained, while allowing access to some of the parameters controlling network performance. Results and DiscussionWe used gastric mill (GM) neurons of the STG of t...

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“…However the picking of the right parameter combinations for the modelling of a given STG neuron remains a problem in general -i.e. to pick parameters such that the model neurons behave realistically individually, when connected in a network, and also when exposed to changes in their neuromodulatory environment such as toxins or external stimulation [12].…”

Section: Below)mentioning

confidence: 99%

Modelling the restoration of activity in a biological neural network

Santos

Steyn

András

2016

2016 International Joint Conference on Neural Networks (IJCNN)

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Abstract-Understanding the mechanisms of restoration of activity in biological neural systems following exposure to damage is key for design of future neuro-prosthetic devices and restorative treatments. The pyloric rhythm network within the crustacean stomatogastric ganglion is a biological neural system that shows spontaneous restoration of activity following the stopping of inputs from higher control ganglia. We model the restoration of the activity in this network using conductancebased models of neurons and the alteration of conductance parameters of the model. Our analysis shows that this approach works only if some of the conductance values remain constrained following the stopping of higher inputs. Our model also shows that in order to model the restoration of the activity in this network it is not necessary to rely on complicated alterations of the mechanisms of Calcium ionic currents in the model, which was proposed previously.

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Models Wagging the Dog: Are Circuits Constructed with Disparate Parameters?

Cited by 34 publications

References 29 publications

Variability, compensation, and modulation in neurons and circuits

Variability, compensation, and modulation in neurons and circuits

Reliable neuromodulation from circuits with variable underlying structure

Modelling the restoration of activity in a biological neural network

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