Whereas neurons may live for scores of years, ion channels and receptors turnover in the membrane in minutes, hours, days or weeks. This means that neurons are constantly rebuilding themselves and neuronal circuits are in a constant state of molecular flux.
Homeostatic mechanisms that help to regulate intrinsic excitability and synaptic strength are needed to stabilize circuit performance.
Computational models have demonstrated that similar activity patterns can be produced by different underlying mechanisms.
Experimental work indicates that the densities of ion channels can vary by as much as two- to fourfold across neurons of the same type in different animals, and that mRNA expression in the same neuron type can also vary in about the same range.
Intuitions about channel function that are developed on the basis of rapid pharmacological manipulations may fail to predict the results of long-term genetic manipulations of the same channel because of slow, compensatory mechanisms.
Much future work is needed to define the combinations of parameters that can give rise to a desired pattern of activity in neurons and networks, to discover the molecular mechanisms that regulate target activity levels, and to uncover the mechanisms by which compensatory regulation of channel expression occurs.
Neurons in most animals live a very long time relative to the half-lives of all of the proteins that govern excitability and synaptic transmission. Consequently, homeostatic mechanisms are necessary to ensure stable neuronal and network function over an animal's lifetime. To understand how these homeostatic mechanisms might function, it is crucial to understand how tightly regulated synaptic and intrinsic properties must be for adequate network performance, and the extent to which compensatory mechanisms allow for multiple solutions to the production of similar behaviour. Here, we use examples from theoretical and experimental studies of invertebrates and vertebrates to explore several issues relevant to understanding the precision of tuning of synaptic and intrinsic currents for the operation of functional neuronal circuits.
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This work was supported by grants from the National Institutes of Health (NIH) and the McDonnell Foundation. We thank L. Abbott for years of conversation about many of these issues and for reading an early version of this manuscript, and P. Baudot for helpful discussions. We are grateful to all the members of the Brandeis University community who have played an important part in the generation of much of the data and many of the ideas presented here.
The authors declare no competing financial interests.
- Synaptic scaling
Process by which neurons regulate the strength of all of their synapses to help maintain a target activity level.
- Conductance densities
The conductance density is conductance divided by surface area. Conductance for a given channel is calculated from the current and reversal potential, and the surface area is estimated from capacitance measurements.
- Transient outward current
(IA). This is caused by a voltage-gated K+ channel that opens when the neuron is depolarized and then inactivates (closes) rapidly. To remove the inactivation, the neuron must be hyperpolarized. IA often plays a part in determining the frequency of action potential firing.
The membrane hyperpolarization that follows an action potential.
- Window currents
A sustained current at a membrane potential that occurs if the voltage dependence of activation and inactivation overlap at that membrane potential.
K+ current active at hyperpolarized membrane potentials that contributes to the resting potential.
- Hyperpolarization/cyclic nucleotide gated channels
(HCN channels). These are a family of mixed cation conductances that activate when the cell is hyperpolarized.
- Inwardly rectifying potassium channels
(Kir2 channels). These are K+ channels that pass inward current much better than outward current. These channels often play an important part in setting the resting potential by contributing an outward current when the neuron is close to its resting potential. However, when the neuron is depolarized, the outward current that develops is less than would be expected from the increase in driving force.
- Pyloric dilator neurons
There are two electrically coupled pyloric dilator neurons in each stomatogastric ganglion. These neurons are also electrically coupled to the anterior burster neuron, and the anterior burster and pyloric dilator neurons together form the pacemaker kernel for the pyloric rhythm. The pyloric dilator neurons are also motor neurons that innervate muscles that dilate the pyloric region of the stomach.
- Long-term potentiation
(LTP). A long-lasting increase in the amplitude of synaptic potentials as a result of specific patterns of presynaptic stimulation. LTP is often thought to be a cellular correlate of changes in networks underlying learning.
- Long-term depression
(LTD). A long-lasting decrease in synaptic strength that is induced by specific patterns of presynaptic activation.
- Synaptic weights
The strengths of synaptic potentials are often called synaptic weights. This term is commonly used in computational and network modelling studies.
- Pyloric rhythm
One of the motor patterns produced by the crustacean stomatogastric ganglion. The pyloric rhythm is an example of a central pattern generator, and consists of an oscillatory motor discharge with a frequency of ∼1 Hz. It is one of the best understood small circuits.
- Half-centre oscillator
An oscillatory circuit produced by reciprocal inhibition. Half-centre oscillators are thought to be important components of many central pattern-generating circuits.
- Lateral pyloric neuron
Each stomatogastric ganglion has a single lateral pyloric neuron, which fires in alternation with the pyloric dilator neurons in the pyloric rhythm. The lateral pyloric neuron provides the only feedback from the pyloric circuit to the pacemaker neurons, and is also a motor neuron that innervates the constrictor muscles of the stomach.
- Central pattern generator
A neural circuit that produces rhythmic motor patterns without requiring timed sensory input.
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Marder, E., Goaillard, JM. Variability, compensation and homeostasis in neuron and network function. Nat Rev Neurosci 7, 563–574 (2006). https://doi.org/10.1038/nrn1949
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