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• W2999974781 startingPage "174" @default.
• W2999974781 abstract "Along sensory pathways, representations of environmental stimuli become increasingly sparse and expanded. If additionally the feed-forward synaptic weights are structured according to the inherent organization of stimuli, the increase in sparseness and expansion leads to a reduction of sensory noise. However, it is unknown how the synapses in the brain form the required structure, especially given the omnipresent noise of environmental stimuli. Here, we employ a combination of synaptic plasticity and intrinsic plasticity—adapting the excitability of each neuron individually—and present stimuli with an inherent organization to a feed-forward network. We observe that intrinsic plasticity maintains the sparseness of the neural code and thereby allows synaptic plasticity to learn the organization of stimuli in low-noise environments. Nevertheless, even high levels of noise can be handled after a subsequent phase of readaptation of the neuronal excitabilities by intrinsic plasticity. Interestingly, during this phase the synaptic structure has to be maintained. These results demonstrate that learning and recalling in the presence of noise requires the coordinated interplay between plasticity mechanisms adapting different properties of the neuronal circuit." @default.
• W2999974781 created "2020-01-23" @default.
• W2999974781 creator A5030076289 @default.
• W2999974781 creator A5084861593 @default.
• W2999974781 date "2020-01-01" @default.
• W2999974781 modified "2023-10-18" @default.
• W2999974781 title "The self-organized learning of noisy environmental stimuli requires distinct phases of plasticity" @default.
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• W2999974781 doi "https://doi.org/10.1162/netn_a_00118" @default.
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• W2999974781 hasPublicationYear "2020" @default.
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