Activity-Dependent Modification of Intrinsic Neuronal Properties

Journal of neurophysiology

I. We describe a new method, the dynamic clamp, that uses a computer as an interactive tool to introduce simulated voltage and ligand mediated conductances into real neurons. 2. We simulate a y-aminobutyric acid (GABA) response of a cultured stomatogastric ganglion neuron to illustrate that the dynamic clamp effectively introduces a conductance into the target neuron. 3. To demonstrate an artificial voltage-dependent conductance, we simulate the action of a voltage-dependent proctolin response on a neuron in the intact stomatogastric ganglion. We show that shifts in the activation curve and the maximal conductance of the response produce different effects on the target neuron. 4. The dynamic clamp is used to construct reciprocal inhibitory synapses between two stomatogastric ganglion neurons that are not coupled naturally, illustrating that this method can be used to form new networks at will.

Journal of Computational Neuroscience

Electrical activity of excitable cells results from ion exchanges through cell membranes, so that genetic or epigenetic changes in genes encoding ion channels are likely to affect neuronal electrical signaling throughout the brain. There is a large literature on the effect of variations in ion channels on the dynamics of spiking neurons that represent the main type of neurons found in the vertebrate nervous systems. Nevertheless, non-spiking neurons are also ubiquitous in many nervous tissues and play a critical role in the processing of some sensory systems. To our knowledge, however, how conductance variations affect the dynamics of non-spiking neurons has never been assessed. Based on experimental observations in the biological literature and on mathematical considerations, we first propose a phenotypic classification of non-spiking neurons. Then, we determine a general pattern of the phenotypic evolution of non-spiking neurons as a function of changes in calcium and potassium conductances. Furthermore, we study the homeostatic compensatory mechanisms of ion channels in a well-posed non-spiking retinal cone model. We show that there is a restricted range of ion conductance values for which the behavior and phenotype of the neuron are maintained.

The Journal of Neuroscience : The Official Journal of the Society for Neuroscience

The Journal of Neuroscience, 1995

We study the electrical activity patterns and the expression of conductances in adult stomatogastric ganglion (STG) neurons as a function of time in primary cell culture. When first plated in culture, these neurons had few active properties. After 1 d in culture they produced small action potentials that rapidly inactivated during maintained depolarization. After 2 d in culture they fired large action potentials tonically when depolarized, and their properties resembled very closely the properties of STG neurons pharmacologically isolated in the ganglion. After 3–4 d in culture, however, their electrical properties changed and they fired in bursts when depolarized. We characterized the currents expressed by these neurons in culture. They included two TTX-sensitive sodium currents, a calcium current, a delayed-rectifier-like current, a calcium-dependent potassium current, and two A-type currents. The changes in firing properties with time in culture were accompanied by an increase in...

Proceedings of the National Academy of Sciences, 2011

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.

Nature Reviews Neuroscience, 2006

Journal of Neuroscience, 2010

Gain modulation is an important feature of neural activity. Previous work has focused on the ability of background synaptic noise to modulate the slope (i.e., gain) of the frequency-current (f-I) relationship in neurons. To date, demonstrations of gain control that are independent of synaptic noise have been limited. We investigated the effects of increasing somatic conductance in the form of tonic inhibition on the initial and steady-state f-I relationship of CA1 pyramidal cells. We find that increasing membrane conductance reduces the gain of the steady-state f-I relationship through a graded increase in the magnitude of spike frequency adaptation. Increased adaptation arises through a conductance-induced depolarization of spike voltage threshold. Thus, by increasing the magnitude of spike frequency adaptation, added conductance can reduce the gain of the steady-state f-I relationship in the absence of random background membrane fluctuations.

BMC Neuroscience, 2009

2006

Neurons exhibit long-term changes in excitability in response to a variety of inputs and perturbations. This plasticity of intrinsic properties is necessary for maintaining proper cell and network activity. The adult crustacean pyloric neuronal network can slowly recover rhythmic activity after complete shutdown resulting from permanent removal of neuromodulatory inputs. We use dissociated stomatogastric ganglion (STG) neurons of the crab Cancer borealis as models to study the mechanisms underlying this process. As observed in a different species, STG neurons spontaneously develop a preferred oscillatory activity pattern via gradual changes in excitability, and rhythmic electrical stimulation can regress oscillatory patterns to less excitable states in some cells. However, we show that rhythmic stimulation can more commonly accelerate the emergence of stable oscillatory patterns in cultured crab STG neurons. We find that both spontaneous and activity-induced oscillations correlate with modifications of the same two ionic currents: a Ca ++ current increase and a high-threshold K + current decrease. Dynamic-clamp experiments confirm that these conductance modifications can explain the observed activity-induced changes. We conclude that the majority of stomatogastric ganglion neurons can become endogenous oscillators and retain this capability into adulthood. However, synaptic interactions or trophic factors may prevent the expression of these oscillations in the intact network. The spontaneous excitability changes observed in isolated neurons may explain the spontaneous recovery of rhythmic activity in the functional network after permanent removal of neuromodulatory input in situ.

Journal of Neurophysiology

AND CONCLUSIONS 1. We have developed a 19-compartment cable model of a guinea pig CA3 pyramidal neuron. Each compartment is allowed to contain six active ionic conductances: gNa, gca, gKcDRJ (where DR stands for delayed rectifier), g,,,, , gktAHP), and gkcc). The conductance gca is of the high-voltage activated type. The model kinetics for the first five of these conductances incorporate voltageclamp data obtained from isolated hippocampal pyramidal neurons. The kinetics of gKcc) are based on data from bullfrog sympathetic neurons. The time constant for decay of submembrane calcium derives from optical imaging of Ca signals in Purkinje cell dendrites.