Consequences of degeneracy in network function
Introduction
Biological ‘degeneracy’ is defined as the ability of elements that are structurally distinct to fulfill the same function, for example, some amino acids are specified by more than one nucleotide combination [1]. This review focuses on degeneracy at a different level, that is, at the level of a neural network. Neural networks are characterized by a set of parameters that describe the intrinsic properties of the component neurons, and the synapses that they make [2]. Degeneracy is observed when more than one set of circuit parameters produces the same (or very similar) output.
Network degeneracy has been described in a number of systems leading to speculation as to why it is observed. It could be beneficial for an organism. Alternatively it could simply reflect the need for tight regulation of network performance without a similar need to restrict specific circuit parameters. We discuss research that strongly argues that network degeneracy makes circuit function more robust. Further, we suggest that network degeneracy can have other functional consequences. We focus on situations in which network activity is configured by persistent effects of neuromodulators, and mechanisms utilized to pattern one bout of activity impact subsequent network activation.
Section snippets
Variability in membrane and synaptic currents
The potential for degeneracy in network function was strikingly illustrated in a computational study that simulated more than 20 million versions of a relatively simple, triphasic motor program generated by the crustacean stomatogastric nervous system [3]. This study clearly demonstrated that virtually indistinguishable activity patterns could arise from widely disparate sets of circuit parameters.
To determine whether degeneracy is observed in biological systems, investigators have measured
Stabilizing effects of conductance correlations
Interestingly, however, a number of studies have demonstrated that this variability can be constrained in that certain circuit parameters co-vary. Namely, the expression levels of different ion channels can be linearly correlated with one another [10, 11, 12]. For example, Schulz et al. [10] measured mRNA expression of the ion channels in each cell type in the crab stomatogastric ganglion (STG) and observed correlations in most neurons, which could be pairwise, three-way or even four-way.
Degeneracy and robustness in behavior
Although a large body of work has demonstrated that degeneracy in ionic conductances can stabilize network activity, much less is known about how this impacts behavior. What is known is primarily a result of research conducted in Caenorhabditis elegans. For instance, C. elegans thermoregulate by modifying navigation, that is, an animal that encounters a temperature higher than its cultivation temperature displays negative thermotaxis [26]. Cell ablation and rescue experiments have demonstrated
Network degeneracy and experience dependent plasticity
In addition to permitting vital behavior under a variety of conditions, degeneracy in network function has been described in other contexts [33, 34•, 35, 36, 37, 38••]. For example, surprising variability in network composition has been reported in large-scale voltage sensitive dye (VSD) imaging experiments monitoring the activity of neural networks mediating highly stereotypic behaviors in molluscs [35, 36, 37, 38••]. Even for a behavior as stereotyped as escape swimming in Tritonia, the
Conclusions
Although a priori it cannot be assumed that degeneracy in network function creates a physiological advantage, data are emerging that suggest that in many cases it does. It is likely that it makes behavior more robust. Further, data suggest that it may be important for the induction of latent memories, and that it may create the potential for increased behavioral flexibility by impacting the dynamics of task switching.
Conflict of interest
Nothing declared.
References and recommended reading
Papers of particular interest, published within the period of review, have been highlighted as:
• of special interest
•• of outstanding interest
Acknowledgements
Supported by NIH grants NS066587, NS070583 and R03DC013997.
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