Abstract
Many forms of synaptic plasticity require the local production of volatile or rapidly diffusing substances such as nitric oxide. The nonspecific plasticity these neuromodulators may induce at neighboring non-active synapses is thought to be detrimental for the specificity of memory storage. We show here that memory retrieval may benefit from this non-specific plasticity when the applied sparse binary input patterns are degraded by local noise. Simulations of a biophysically realistic model of a cerebellar Purkinje cell in a pattern recognition task show that, in the absence of noise, leakage of plasticity to adjacent synapses degrades the recognition of sparse static patterns. However, above a local noise level of 20%, the model with nonspecific plasticity outperforms the standard, specific model. The gain in performance is greatest when the spatial distribution of noise in the input matches the range of diffusion-induced plasticity. Hence non-specific plasticity may offer a benefit in noisy environments or when the pressure to generalize is strong.
Highlights
Many forms of synaptic plasticity require the local production of volatile or rapidly diffusing substances such as nitric oxide
We examined the effect of leakage of plasticity on the recognition of sparse, binary and stationary input patterns disrupted by local noise, in both a linear artificial neural network unit and a morphologically realistic conductance-based Purkinje cell (PC) model (Table 1)
A hundred such patterns were stored by long-term depression (LTD) of the parallel fibres (PFs) synapses using one-shot supervised Hebbian learning[5,17] (Fig. 1a). (In the Mathematical Appendix in Supplementary Information, we show analytically that slightly potentiating the non-depressed synapses does not alter the characteristics of the learning rules)
Summary
Many forms of synaptic plasticity require the local production of volatile or rapidly diffusing substances such as nitric oxide The nonspecific plasticity these neuromodulators may induce at neighboring nonactive synapses is thought to be detrimental for the specificity of memory storage. We show here that memory retrieval may benefit from this non-specific plasticity when the applied sparse binary input patterns are degraded by local noise. The sparse activity of the granular layer enhances the storage capacity of the Purkinje cell (defined as the number of PF patterns that can be stored without intolerable error)[3,9,17,18,19,20]. More importantly, LTD at the parallel-fibre-to-Purkinje-cell synapse requires the production and release of NO by PFs24,25 This NO diffuses to neighboring synapses and compromises the synapse specificity of LTD26–33. A recent theoretical study predicted that such non-specific plasticity would be detrimental for memory[34]
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