 The anatomical organization of the cerebellum provides a clear example of a network amenable to this computational interpretation. Consider  Figure 1.  The cerebellum is the bulbous convoluted structure dorsal to the brainstem. A variety of studies (behavioral, neuropsychological, single-cell electrophysiological) implicate this structure in motor integration and fine motor coordination. Mossy fibers (axons) from neurons outside the cerebellum synapse on cerebellar granule cells, which in turn project to parallel fibers. Activity patterns across the collection of mossy fibers (frequency of action potentials per time unit in each fiber projecting into the cerebellum) provide values for the input vector. Parallel fibers make multiple synapses on the dendritic trees and cell bodies of cerebellular Purkinje neurons. Each Purkinje neuron “sums” its post-synaptic potentials (PSPs) and emits a train of action potentials down its axon based (partly) on its total input and previous activation state. Purkinje axons project outside the cerebellum. The network’s output vector is thus the ordered values representing the pattern of activity generated in each Purkinje axon. Changes to the efficacy of individual synapses on the parallel fibers and the Purkinje neurons alter the resulting PSPs in Purkinje axons, generating different axonal spiking frequencies. Computationally, this amounts to a different output vector to the same input activity  pattern—plasticity.[4]