Synaptic Transmission Optimization Predicts Expression Loci of Long-Term Plasticity
Long-term modifications of neuronal connections are critical for reliable memory storage in the brain. However, their locus of expression—pre- or postsynaptic—is highly variable. Here we introduce a theoretical framework in which long-term plasticity performs an optimization of the postsynaptic resp...
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Veröffentlicht in: | Neuron (Cambridge, Mass.) Mass.), 2017-09, Vol.96 (1), p.177-189.e7 |
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Zusammenfassung: | Long-term modifications of neuronal connections are critical for reliable memory storage in the brain. However, their locus of expression—pre- or postsynaptic—is highly variable. Here we introduce a theoretical framework in which long-term plasticity performs an optimization of the postsynaptic response statistics toward a given mean with minimal variance. Consequently, the state of the synapse at the time of plasticity induction determines the ratio of pre- and postsynaptic modifications. Our theory explains the experimentally observed expression loci of the hippocampal and neocortical synaptic potentiation studies we examined. Moreover, the theory predicts presynaptic expression of long-term depression, consistent with experimental observations. At inhibitory synapses, the theory suggests a statistically efficient excitatory-inhibitory balance in which changes in inhibitory postsynaptic response statistics specifically target the mean excitation. Our results provide a unifying theory for understanding the expression mechanisms and functions of long-term synaptic transmission plasticity.
•A theory of synaptic plasticity that predicts pre- and postsynaptic expression loci•The framework captures LTP and LTD data across different experiments and brain regions•Variability of pre/post changes due to optimizing postsynaptic response statistics•Optimization at inhibitory synapses suggests a statistically optimal E/I balance
For decades the variability in expression loci of long-term synaptic plasticity has remained enigmatic. Costa et al. propose a theory in which this variability is a consequence of postsynaptic response optimization, consistent with a wide range of experimental observations. |
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ISSN: | 0896-6273 1097-4199 |
DOI: | 10.1016/j.neuron.2017.09.021 |