Neural processing of noisy inputs

Neurons are inherently noisy.  This means the inputs to each neural system are made somewhat ambiguous or unreliable because of neural noise.  What sorts of adaptations exist in neural system to cope with and improve performance in the face of noisy and unreliable inputs?  Large-scale computer simulations of the cerebellum are used by the Mauk lab to investigate these questions in the cerebellum, a brain system well-enough understood to address such advanced questions.  Recent discoveries point to highly adaptive processes implemented by the cerebellum to ensure that noisy inputs do not translate into non-adaptive outputs.  These mechanisms involve feedback, a ubiquitous aspect of neural architectures that is poorly understood.