Despite the widespread distribution of inhibitory synapses throughout the central nervous system, plasticity of inhibitory synapses related to associative learning has never been reported. In the cerebellum, the neural correlate of fear memory is provided by a long-term potentiation (LTP) of the excitatory synapse between the parallel fibers (PFs) and the Purkinje cell (PC). In this article, we provide evidence that inhibitory synapses in the cerebellar cortex also are affected by fear conditioning. Whole-cell patch-clamp recordings of spontaneous and miniature GABAergic events onto the PC show that the frequency but not the amplitude of these events is significantly greater up to 24 h after the conditioning. Adequate levels of excitation and inhibition are required to maintain the temporal fidelity of a neuronal network. Such fidelity can be evaluated by determining the time window for multiple input coincidence detection. We found that, after fear learning, PCs are able to integrate excitatory inputs with greater probability within short delays, but the width of the whole window is unchanged. Therefore, excitatory LTP provides a more effective detection, and inhibitory potentiation serves to maintain the time resolution of the system.
Learning-related long-term potentiation of inhibitory synapses in the cerebellar cortex.
SACCHETTI, Benedetto;STRATA, Pier Giorgio
2008-01-01
Abstract
Despite the widespread distribution of inhibitory synapses throughout the central nervous system, plasticity of inhibitory synapses related to associative learning has never been reported. In the cerebellum, the neural correlate of fear memory is provided by a long-term potentiation (LTP) of the excitatory synapse between the parallel fibers (PFs) and the Purkinje cell (PC). In this article, we provide evidence that inhibitory synapses in the cerebellar cortex also are affected by fear conditioning. Whole-cell patch-clamp recordings of spontaneous and miniature GABAergic events onto the PC show that the frequency but not the amplitude of these events is significantly greater up to 24 h after the conditioning. Adequate levels of excitation and inhibition are required to maintain the temporal fidelity of a neuronal network. Such fidelity can be evaluated by determining the time window for multiple input coincidence detection. We found that, after fear learning, PCs are able to integrate excitatory inputs with greater probability within short delays, but the width of the whole window is unchanged. Therefore, excitatory LTP provides a more effective detection, and inhibitory potentiation serves to maintain the time resolution of the system.File | Dimensione | Formato | |
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