The dynamic clamp: artificial conductances in biological neurons

doi:10.1016/0166-2236(93)90004-6

Trends in Neurosciences

Volume 16, Issue 10, October 1993, Pages 389-394

https://doi.org/10.1016/0166-2236(93)90004-6 Get rights and content

Abstract

The dynamic clamp is a novel method that uses computer simulation to introduce conductances into biological neurons. This method can be used to study the role of various conductances in shaping the activity of single neurons, or neurons within networks. The dynamic clamp can also be used to form circuits from previously unconnected neurons. This approach makes computer simulation an interactive experimental tool, and will be useful in many applications where the role of synaptic strengths and intrinsic properties in neuronal and network dynamics is of interest.

References (17)

E. Marder et al.
D. Kleinfeld et al.
Biophys. J.
(1990)
A.G.M. Bulloch et al.
Trends Neurosci.
(1992)
A.L. Hodgkin et al.
J. Physiol.
(1952)
A.A. Sharp et al.
J. Neurophysiol.
(1993)
Marder, E. et al. in Enabling Technologies For Cultured Neural Networks (Stenger, D. A. and McKenna, T. M., eds),...
S. Renaud-LeMasson et al.
J. Golowasch et al.
J. Neurosci.
(1992)

There are more references available in the full text version of this article.

Cited by (243)

Deconstructing the integrated oscillator model for pancreatic β-cells
2023, Mathematical Biosciences
Electrical bursting oscillations in the $β$ -cells of pancreatic islets have been a focus of investigation for more than fifty years. This has been aided by mathematical models, which are descendants of the pioneering Chay–Keizer model. This article describes the key biophysical and mathematical elements of this model, and then describes the path forward from there to the Integrated Oscillator Model (IOM). It is both a history and a deconstruction of the IOM that describes the various elements that have been added to the model over time, and the motivation for adding them. Finally, the article is a celebration of the 40th anniversary of the publication of the Chay–Keizer model.
A design principle of spindle oscillations in mammalian sleep
2022, iScience
Neural oscillations are mainly regulated by molecular mechanisms and network connectivity of neurons. Large-scale simulations of neuronal networks have driven the population-level understanding of neural oscillations. However, cell-intrinsic mechanisms, especially a design principle, of neural oscillations remain largely elusive. Herein, we developed a minimal, Hodgkin-Huxley-type model of groups of neurons to investigate molecular mechanisms underlying spindle oscillation, which is synchronized oscillatory activity predominantly observed during mammalian sleep. We discovered that slowly inactivating potassium channels played an essential role in characterizing the firing pattern. The detailed analysis of the minimal model revealed that leak sodium and potassium channels, which controlled passive properties of the fast variable (i.e., membrane potential), competitively regulated the base value and time constant of the slow variable (i.e., cytosolic calcium concentration). Consequently, we propose a theoretical design principle of spindle oscillations that may explain intracellular mechanisms behind the flexible control over oscillation density and calcium setpoint.
Perturbation-specific responses by two neural circuits generating similar activity patterns
2021, Current Biology
A fundamental question in neuroscience is whether neuronal circuits with variable circuit parameters that produce similar outputs respond comparably to equivalent perturbations.1, 2, 3, 4 Work on the pyloric rhythm of the crustacean stomatogastric ganglion (STG) showed that highly variable sets of intrinsic and synaptic conductances can generate similar circuit activity patterns.5, 6, 7, 8, 9 Importantly, in response to physiologically relevant perturbations, these disparate circuit solutions can respond robustly and reliably,10, 11, 12 but when exposed to extreme perturbations the underlying circuit parameter differences produce diverse patterns of disrupted activity.⁷^,¹²^,¹³ In this example, the pyloric circuit is unchanged; only the conductance values vary. In contrast, the gastric mill rhythm in the STG can be generated by distinct circuits when activated by different modulatory neurons and/or neuropeptides.14, 15, 16, 17, 18, 19, 20, 21 Generally, these distinct circuits produce different gastric mill rhythms. However, the rhythms driven by stimulating modulatory commissural neuron 1 (MCN1) and bath-applying CabPK (Cancer borealis pyrokinin) peptide generate comparable output patterns, despite having distinct circuits that use separate cellular and synaptic mechanisms.22, 23, 24, 25 Here, we use these two gastric mill circuits to determine whether such circuits respond comparably when challenged with persisting (hormonal: CCAP) or acute (sensory: GPR neuron) metabotropic influences. Surprisingly, the hormone-mediated action separates these two rhythms despite activating the same ionic current in the same circuit neuron during both rhythms, whereas the sensory neuron evokes comparable responses despite acting via different synapses during each rhythm. These results highlight the need for caution when inferring the circuit response to a perturbation when that circuit is not well defined physiologically.
Autonomic learning via saturation gain method, and synchronization between neurons
2020, Chaos, Solitons and Fractals
Citation Excerpt :
Biological neurons [1–3] show distinct self-adaption and a variety of modes in neural activities can be generated by applying external stimulus, which can change the excitability of neurons.
Synchronization provides an effective way for stable signal exchange and balance in membrane potentials of neurons. Both electric synapse and chemical synapse play important role in processing signals by emitting signal and receiving signals, and the encoded signals are estimated by a variety of synaptic currents. For two or more neurons, the synaptic current can pass along the coupling channels with feasible self-adaption and then synaptic plasticity is formed. The occurrence of synaptic currents generates complex biophysical effect because continuous propagation and pumping of calcium, sodium and potassium can induce time-varying physical field intra- and extracellular of cell. Indeed, the field effect becomes more distinct when more neurons are involved in a functional region of the nervous system. To decrease the energy consumption and obtain fast signal exchange, autonomic learning is often activated to select the most appropriate coupling gain in the synapses connected to neurons. That is, synapse can increase the synaptic intensity carefully before reaching synchronization. In this paper, the two-variable Fitzhugh-Nagumo neuron driven by voltage source is used to investigate the synchronization stability when hybrid synapse is applied between two neurons. By using the saturation gain method, the synapse intensity is increased with appropriate step until synchronization is reached, and then the coupling intensity is fixed to find the threshold for stabilizing complete synchronization. It gives new clues to understand the synaptic plasticity from physical viewpoint.
Reduced intrinsic excitability of CA1 pyramidal neurons in human immunodeficiency virus (HIV) transgenic rats
2019, Brain Research
Citation Excerpt :
The Cm of neurons in the ventral hippocampus was 140.1 ± 16.22 pF vs. 150.8 ± 18.25 pF in control and HIV Tg rats, respectively (n = 13–15). The dynamic clamp method allows the dynamic control of the injected current with the purpose of better reproducing natural synaptic inputs in neurons (Chance and Abbott, 2009; Economo et al., 2010; Robinson and Kawai, 1993; Sharp et al., 1993). The current that is injected into the cell membrane using the dynamic clamp is calculated using computation methods and then readjusted with a high frequency (>10 kHz) to take into account the continuously changing membrane potential of the neuron (Chance and Abbott, 2009; Economo et al., 2010).
The hippocampus is involved in key neuronal circuits that underlie cognition, memory, and anxiety, and it is increasingly recognized as a vulnerable structure that contributes to the pathogenesis of HIV-associated neurocognitive disorder (HAND). However, the mechanisms responsible for hippocampal dysfunction in neuroHIV remain unknown. The present study used HIV transgenic (Tg) rats and patch-clamp electrophysiological techniques to study the effects of the chronic low-level expression of HIV proteins on hippocampal CA1 pyramidal neurons. The dorsal and ventral areas of the hippocampus are involved in different neurocircuits and thus were evaluated separately. We found a significant decrease in the intrinsic excitability of CA1 neurons in the dorsal hippocampus in HIV Tg rats by comparing neuronal spiking induced by current step injections and by dynamic clamp to simulate neuronal spiking activity. The decrease in excitability in the dorsal hippocampus was accompanied by a higher rate of excitatory postsynaptic currents (EPSCs), whereas CA1 pyramidal neurons in the ventral hippocampus in HIV Tg rats had higher EPSC amplitudes. We also observed a reduction of hyperpolarization-activated nonspecific cationic current (I_h) in both the dorsal and ventral hippocampus. Neurotoxic HIV proteins have been shown to increase neuronal excitation. The lower excitability of CA1 pyramidal neurons that was observed herein may represent maladaptive homeostatic plasticity that seeks to stabilize baseline neuronal firing activity but may disrupt neural network function and contribute to HIV-associated neuropsychological disorders, such as HAND and depression.
Multiplicative noise is beneficial for the transmission of sensory signals in simple neuron models
2019, BioSystems
Citation Excerpt :
On the other hand, a signal that enters through a rate modulation will naturally also come along with a voltage-dependent amplitude, hence we have to deal not only with a multiplicative noise but also with a multiplicative signal. An experimental test of our predictions might be feasible via the dynamic-clamp techniques (Sharp et al., 1993; Prinz et al., 2004) by which arbitrary conductances can be mimicked via current injections into a neuron in vitro. Testing whether an appropriate change in reversal potentials can lead to an improved signal transmission would be similar to our approach and does not seem to be (conceptually!)
We study simple integrate-and-fire type models with multiplicative noise and consider the transmission of a weak and slow signal, i.e. a signal that evokes a small modulation of the instantaneous firing rate on time scales that are much larger than the membrane time scale and the mean interspike interval. The specific question of interest is whether and how the state-dependence of the noise can be optimized with respect to information transmission. First, in a simple model in which the noise intensity varies linearly with the state variable, we show analytically that multiplicative fluctuations may benefit the signal transfer and we elucidate the mechanism for this improvement. In a conductance-based integrate-and-fire model with synaptically filtered shot-noise input, we show by means of extended numerical simulations that also in a biophysically more relevant situation, multiplicative noise can enhance the signal-to-noise ratio. Our results shed light on a so far unexplored aspect of stochastic signal transmission in neural systems.

View all citing articles on Scopus

View full text

Trends in Neurosciences

TechniquesThe dynamic clamp: artificial conductances in biological neurons

Abstract

Biophys. J.

Trends Neurosci.

J. Physiol.

J. Neurophysiol.

J. Neurosci.

Techniques
The dynamic clamp: artificial conductances in biological neurons