  Some biological systems operate at the critical point between stability and
instability and this requires a fine-tuning of parameters. We bring together
two examples from the literature that illustrate this: neural integration in
the nervous system and hair cell oscillations in the auditory system. In both
examples the question arises as to how the required fine-tuning may be achieved
and maintained in a robust and reliable way. We study this question using tools
from nonlinear and adaptive control theory. We illustrate our approach on a
simple model which captures some of the essential features of neural
integration. As a result, we propose a large class of feedback adaptation rules
that may be responsible for the experimentally observed robustness of neural
integration. We mention extensions of our approach to the case of hair cell
oscillations in the ear.

Optimization and Control;Neurons and Cognition