Figure 1.
Emulation of eyelid conditioning in a computer simulation of the cerebellum. (A) A schematic representation of the simulation and how it was trained using an eyelid conditioning-like protocol. The output of the simulation comes from the summed activity of the six cerebellar deep nucleus cells (blue box). The CS was conveyed to the simulation by phasic activation of 18 of the 600 mossy fibers and tonic activation of six mossy fibers (green box). The US was emulated by a brief excitatory conductance applied to the single climbing fiber. The remainder of the simulation consisted of 10,000 granule cells, 900 Golgi cells, 20 stellate/basket cells, and 20 Purkinje cells with essentials of the connectivity as shown. (B) Acquisition, extinction, and savings by the simulation. Each panel shows the equivalent of 10 d of acquisition (left panel), extinction (center), and reacquisition (right) training. Individual sweeps are averages of 10 trials, which are clustered together to approximate the equivalent of one daily session of eyelid conditioning. These sessions are numbered at the left, progressing from front to back. The blue portion of the sweeps denotes the presence of the CS. (C) The strength of the mossy fiber-to-nucleus synapses in the simulation over the three phases of training. The synapses that progressively increase in strength during acquisition and reacquisition and decrease during extinction are the six that are tonically activated by the CS. Note that extinction training only slowly and thus incompletely reverses the strengthened synapses. Savings during reacquisition in the simulation is largely attributable to this residual plasticity. The continued increase in the strength of these synapses does not produce a comparable increase in response amplitude, rather, it reflects the tendency for the network to transfer plasticity from cortex (pauses in Purkinje activity produced by LTD) to the nucleus (increased strength of mossy fiber-to-nucleus synapses). How long this process continues depends on a number of unknown factors.