A real-time model of the cerebellar circuitry underlying classical conditioning: A combined simulation and robotics study

Abstract Although key components of the cerebellar circuitry relevant to classical conditioning have been identified, the question how they act together is still unresolved. In this simulation study, we investigate a real-time model which captures basic anatomical and physiological properties of this system. We show that this model displays realistic learning performance over a range of inter-stimulus intervals, and demonstrate its stability using a mobile robot solving an obstacle avoidance task.

[1]  Paul F. M. J. Verschure,et al.  A bottom up approach towards the acquisition and expression of sequential representations applied to a behaving real-world device: Distributed Adaptive Control III , 1998, Neural Networks.

[2]  R. F. Thompson,et al.  Inhibitory cerebello-olivary projections and blocking effect in classical conditioning. , 1998, Science.

[3]  Paul F. M. J. Verschure,et al.  What Can Robots Tell Us About Brains? A Synthetic Approach Towards the Study of Learning and Problem Solving , 1999, Reviews in the neurosciences.

[4]  S. Grossberg,et al.  Metabotropic Glutamate Receptor Activation in Cerebellar Purkinje Cells as Substrate for Adaptive Timing of the Classically Conditioned Eye-Blink Response , 1996, The Journal of Neuroscience.

[5]  H. Roitblat,et al.  Categorization , Representations , and the Dynamics of System-Environment Interaction : a case study in autonomous systems , 1992 .

[6]  Paul F. M. J. Verschure,et al.  Categorization, representations, and the dynamics of system-environment interaction: a case study in autonomous systems , 1993 .

[7]  D. Marr.  A theory of cerebellar cortex , 1969, The Journal of physiology.

[8]  R. F. Thompson,et al.  Mammalian brain substrates of aversive classical conditioning. , 1993, Annual review of psychology.

[9]  G. Hesslow.  Correspondence between climbing fibre input and motor output in eyeblink‐related areas in cat cerebellar cortex. , 1994, The Journal of physiology.

[10]  Paul F. M. J. Verschure,et al.  Local and Global Gating of Synaptic Plasticity , 2000, Neural Computation.

[11]  M. Sakurai.  Synaptic modification of parallel fibre‐Purkinje cell transmission in in vitro guinea‐pig cerebellar slices. , 1987, The Journal of physiology.

[12]  J. Albus.  A Theory of Cerebellar Function , 1971 .