Purkinje cells can encode the strength of parallel fiber inputs in their firing by using 2 fundamentally different mechanisms, either as pauses or as linear increases in firing rate. It is not clear which of these 2 encoding mechanisms is used by the cerebellum. We used the pattern-recognition capacity of Purkinje cells based on the Marr-Albus-Ito theory of cerebellar learning to evaluate the suitability of the linear algorithm for cerebellar information processing. Here, we demonstrate the simplicity and versatility of pattern recognition in Purkinje cells linearly encoding the strength of parallel fiber inputs in their firing rate. In contrast to encoding patterns with pauses, Purkinje cells using the linear algorithm could recognize a large number of both synchronous and asynchronous input patterns in the presence or absence of inhibitory synaptic transmission. Under all conditions, the number of patterns recognized by Purkinje cells using the linear algorithm was greater than that achieved by encoding information in pauses. Linear encoding of information also allows neurons of deep cerebellar nuclei to use a simple averaging mechanism to significantly increase the computational capacity of the cerebellum. We propose that the virtues of the linear encoding mechanism make it well suited for cerebellar computation.cerebellum ͉ motor learning ͉ Purkinje cell P urkinje cells receive Ͼ150,000 parallel fiber synaptic inputs (1) that provide them with a vast and broad spectrum of information. These inputs are integrated with the spontaneous activity of Purkinje cells to provide the sole output of the computational circuitry of the cerebellar cortex. The mechanism by which this information is encoded by Purkinje cells is fundamental to theories of cerebellar computation. It has been recently demonstrated that Purkinje cells can encode this information by using 2 different mechanisms (2), either as pauses in their activity (3) or as linear increases in their firing rate (4) (see also Fig. 1B). Although, in principle, cerebellar computation can be based on either of these 2 encoding schemes, it is unlikely that they are used concurrently because they require fundamentally different decoding mechanisms. It has not been established whether either of these 2 mechanisms is used by the cerebellum, nor is it even known how they directly compare in their ability to encode information.Pattern recognition was proposed in a pair of seminal papers by Marr and Albus (5, 6) to be the mechanism by which cerebellar Purkinje cells learn motor tasks. Based on this theory, the more patterns the cerebellum recognizes, the higher its computational power and ability to fine-tune and learn motor tasks. Numerous attempts have been made to estimate the pattern recognition capacity of Purkinje cells (3,(5)(6)(7)(8), and recently it has been used to evaluate the suitability of an encoding mechanism in cerebellar computation (3).A recent evaluation of a detailed Purkinje cell model suggested that optimal pattern recognition capacity is obtained ...