Beyond Optimality: Variability, Homeostasis and Modulation of Rhythmic Neuronal Circuits Eve Marder (Brandeis)
Neurons and networks must constantly rebuild themselves in response to the continual and ongoing turnover of all of the ion channels and receptors that are necessary for neuronal signaling. A good deal of work argues that stable neuronal and network function arises from homeostatic negative feedback mechanisms. Nonetheless, while these mechanisms can produce a target activity or performance, they are also consistent with a good deal of recent theoretical and experimental work that shows that similar circuit outputs can be produced with highly variable circuit parameters. This work argues that the nervous system of each healthy individual has found a set of different solutions that give “good enough circuit performance. Studies using the crustacean stomatogastric nervous system argue that synaptic and intrinsic currents can vary far more than the output of the circuit in which they are found. These data have significant implications for the mechanisms that maintain stable function over the animal’s lifetime, and for the kinds of changes that allow the nervous system to recover function after injury. In this kind of complex system, merely collecting mean data from many individuals can lead to significant errors, and it becomes important to measure as many individual network parameters in each individual as possible. Moreover, I argue that it is more appropriate to develop families of models, rather than a singly, highly-tuned model, to characterize the dynamics of any given neuron or network, so that the model distribution captures the distributions in the biological systems to be modeled. Supported by MH 46742 and NS 17813.