title: Evaluating the adaptive-filter model of the cerebellum.
abstract: The adaptive-filter model of the cerebellar microcircuit is in widespread use, combining as it does an explanation of key microcircuit features with well-specified computational power. Here we consider two methods for its evaluation. One is to test its predictions concerning relations between cerebellar inputs and outputs. Where the relevant experimental data are available, e.g. for the floccular role in image stabilization, the predictions appear to be upheld. However, for the majority of cerebellar microzones these data have yet to be obtained. The second method is to test model predictions about details of the microcircuit. We focus on features apparently incompatible with the model, in particular non-linear patterns in Purkinje cell simple-spike firing. Analysis of these patterns suggests the following three conclusions. (i) It is important to establish whether they can be observed during task-related behaviour. (ii) Highly non-linear models based on these patterns are unlikely to be universal, because they would be incompatible with the (approximately) linear nature of floccular function. (iii) The control tasks for which these models are computationally suited need to be identified. At present, therefore, the adaptive filter remains a candidate model of at least some cerebellar microzones, and its evaluation suggests promising lines for future enquiry.
authors.affiliation: Department of Psychology, University of Sheffield, Western Bank, Sheffield S10 2TP, UK. p.dean@sheffield.ac.uk
authors.forename: Paul
authors.initials: P
authors.lastname: Dean
authors.forename: John
authors.initials: J
authors.lastname: Porrill
mesh_terms: D000465:Algorithms; D000818:Animals; D002531:Cerebellum / Q000502:physiology*; D003198:Computer Simulation; D006801:Humans; D008959:Models, Neurological; D009043:Motor Activity / Q000502:physiology*; D009415:Nerve Net / Q000502:physiology*