In contrast to other fields in biology, mathematical thinking and methodology have become entrenched in neuroscience since its very beginning, as witnessed by the classical work of Hodgkin and Huxley. Indeed, important developments in mathematics, and particularly in statistics (for example, point processes theory), have their roots in this field.

One of the biggest open challenges mathematicians and engineers face, is understanding the complex computation that takes place in our brain. Among the most interesting parts of the brain, is the `little brain’, otherwise known as the cerebellum. The cerebellum is of critical importance for sensory-motor control and learning and its disruption causes a dramatic neurological syndrome called ataxia. The granular layer forms the input stage of the cerebellum in which information coming from the peripheral and central systems converge through the mossy fibers. The granular layer has by far the smallest(∼ 5μm) and the most numerous neurons(∼ 10^11 ) in humans. Understanding how the granular layer process information appears critical to understand the cerebellar function, since signals coming into upper cortical layers are provided by the granular layer.

Current focus in theoretical neuroscience studies here at ASBT is the detailed modeling of cerebellar cells and its network functions.