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  Burst-time-dependent plasticity robustly guides ON/OFF segregation in the lateral geniculate nucleus

Gjorgjieva, J., Toyoizumi, T., & Eglen, S. J. (2009). Burst-time-dependent plasticity robustly guides ON/OFF segregation in the lateral geniculate nucleus. PLoS Comput Biol, 5(12):. doi:10.1371/journal.pcbi.1000618.

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アイテムのパーマリンク: https://hdl.handle.net/21.11116/0000-0008-0D63-B 版のパーマリンク: https://hdl.handle.net/21.11116/0000-0008-7B4C-A
資料種別: 学術論文

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https://www.ncbi.nlm.nih.gov/pubmed/20041207 (全文テキスト(全般))
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 作成者:
Gjorgjieva, Julijana1, 著者           
Toyoizumi, T., 著者
Eglen, S. J., 著者
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1Computation in Neural Circuits Group, Max Planck Institute for Brain Research, Max Planck Society, ou_2461694              

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キーワード: Action Potentials/*physiology Animals Computer Simulation Geniculate Bodies/*physiology Mice *Models, Neurological Nerve Net/*physiology Neural Inhibition/physiology Neuronal Plasticity/*physiology Retinal Ganglion Cells/*physiology Visual Perception/*physiology
 要旨: Spontaneous retinal activity (known as "waves") remodels synaptic connectivity to the lateral geniculate nucleus (LGN) during development. Analysis of retinal waves recorded with multielectrode arrays in mouse suggested that a cue for the segregation of functionally distinct (ON and OFF) retinal ganglion cells (RGCs) in the LGN may be a desynchronization in their firing, where ON cells precede OFF cells by one second. Using the recorded retinal waves as input, with two different modeling approaches we explore timing-based plasticity rules for the evolution of synaptic weights to identify key features underlying ON/OFF segregation. First, we analytically derive a linear model for the evolution of ON and OFF weights, to understand how synaptic plasticity rules extract input firing properties to guide segregation. Second, we simulate postsynaptic activity with a nonlinear integrate-and-fire model to compare findings with the linear model. We find that spike-time-dependent plasticity, which modifies synaptic weights based on millisecond-long timing and order of pre- and postsynaptic spikes, fails to segregate ON and OFF retinal inputs in the absence of normalization. Implementing homeostatic mechanisms results in segregation, but only with carefully-tuned parameters. Furthermore, extending spike integration timescales to match the second-long input correlation timescales always leads to ON segregation because ON cells fire before OFF cells. We show that burst-time-dependent plasticity can robustly guide ON/OFF segregation in the LGN without normalization, by integrating pre- and postsynaptic bursts irrespective of their firing order and over second-long timescales. We predict that an LGN neuron will become ON- or OFF-responsive based on a local competition of the firing patterns of neighboring RGCs connecting to it. Finally, we demonstrate consistency with ON/OFF segregation in ferret, despite differences in the firing properties of retinal waves. Our model suggests that diverse input statistics of retinal waves can be robustly interpreted by a burst-based rule, which underlies retinogeniculate plasticity across different species.

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 日付: 2009-12-31
 出版の状態: 出版
 ページ: -
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 識別子(DOI, ISBNなど): その他: 20041207
DOI: 10.1371/journal.pcbi.1000618
ISSN: 1553-7358 (Electronic)1553-734X (Linking)
 学位: -

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出版物名: PLoS Comput Biol
種別: 学術雑誌
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ページ: - 巻号: 5 (12) 通巻号: e1000618 開始・終了ページ: - 識別子(ISBN, ISSN, DOIなど): -