document: A scalable model of cerebellar adaptive timing and sequencing : the recurrent slide and latch -LRB- RSL -RRB- model From the dawn of modern neural network theory , the mammalian cerebellum has been a favored object of mathematical modeling studies . Early studies focused on the fanout , convergence , thresholding , and learned weighting of perceptual-motor signals within the cerebellar cortex . This led to the still viable idea that the granule cell stage in the cerebellar cortex performs a sparse expansive recoding of the time-varying input vector . This recoding reveals and emphasizes combinations in a distributed representation that serves as a basis for the learned , state-dependent control actions engendered by cerebellar outputs to movement related centers . To make optimal use of available signals , the cerebellum must be able to sift the evolving state representation for the most reliable predictors of the need for control actions , and to use those predictors even if they appear only transiently and well in advance of the optimal time for initiating the control action . The paper proposes a modification to prior , population , models for cerebellar adaptive timing and sequencing . Since it replaces a population with a single element , the proposed RSL model is in one sense maximally efficient , and therefore optimal from the perspective of scalability
doc_bio_tags: O B I O B I I O O O O O O O O O O O O O O O O O B I I O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O B I I O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O
extractive_keyphrases: scalable model cerebellar adaptive timing neural network theory mammalian cerebellum granule cell stage sparse expansive recoding distributed representation
abstractive_keyphrases: cerebellar sequencing recurrent slide and latch model time-varying input vector recurrent network