Award details

Cerebellum as a neuronal machine: Behavioural electrophysiological and computational analysis of classical conditioning

Reference	BBS/B/17026
Principal Investigator / Supervisor	Emeritus Professor Paul Dean
Co-Investigators / Co-Supervisors	Professor John Porrill
Institution	University of Sheffield
Department	Psychology
Funding type	Research
Value (£)	184,698
Status	Completed
Type	Research Grant
Start date	01/12/2004
End date	30/11/2007
Duration	36 months

Abstract

The cerebellum has been likened to a neuronal machine making critical contributions to sensory-motor control, motor learning and cognition. Its cortical neurons are in a regularly repeating, geometrical array that suggests an information-processing algorithm consistent across every region. Classical conditioning of the eyeblink response is an excellent model of associative learning and recent work has defined cerebellar circuitry essential for its learning and expression. These advances provide an outstanding opportunity to analyse an identified neural network operating under natural conditions to develop a specified measurable learned behaviour. Three laboratories will work closely together to characterise the cerebellar algorithm using behavioural/pharmacological, multiple single-unit electrophysiology and computational methods. (Joint with BBS/B/1700X and BBS/B/16984).

Summary

unavailable

Committee	Closed Committee - Animal Sciences (AS)
Research Topics	X – not assigned to a current Research Topic
Research Priority	X – Research Priority information not available
Research Initiative	Integrative Analysis of Brain and Behaviour (IABB) [2003]
Funding Scheme	X – not Funded via a specific Funding Scheme

Associated awards:

BBS/B/16984 Cerebellum as a neuronal machine: Behavioural electrophysiological and computational analysis of classical conditioning

BBS/B/1700X Cerebellum as a neuronal machine: Behavioural electrophysiological and computational analysis of classical conditioning

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