Reversal and Stabilization of Synaptic Modifications in a Developing Visual System

By Qiang Zhou, Hui-zhong W. Tao, Mu-Ming Poo. 2003

166 citations recorded by the source corpus.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience, Electrical and Electronic Engineering

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In Cellular and Molecular Neuroscience

In Cognitive Neuroscience

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Citations in the corpus

The temporal paradox of Hebbian learning and homeostatic plasticity (2017, background): “For instance, [83] demonstrated via dynamic-clamp that a simulated increase in total excitatory and inhibitory background conductance, which could originate from elevated levels of network activity, rapidly reduces the amplitude of LTP, but not LTD, of the STDP window.”
Axon retraction and degeneration in development and disease. (2005, background): “In the primary visual area (V1) of the cortex, geniculocortical axons from the eye-specific layers of the dLGN are segregated into eye-specific stripes or columns in layer 4.”
Cascade models of synaptically stored memories. (2005, background): “A prominent one is the difference in memory performance and longterm synaptic potentiation between massed and spaced training paradigms (Mauelshagen et al., 1998; Hermitte et al., 1999; Menzel et al., 2001; Wu et al., 2001; Sutton et al., 2002; Scharf et al., 2002; Woo et al., 2003; Zhou et al., 200”
Computational principles of biological memory (2015, background): “This phenomenon has been observed in several behavioral studies (see e.g. Anderson, 1995) and more recently in electrophysiology experiments on synaptic plasticity (see e.g. Carew et al., 1972; Zhou et al., 2003).”
Continual Learning Through Synaptic Intelligence (2017, background): “Finally, recent synaptic changes can be reset by stereotypical neural activity, whereas older synaptic memories become increasingly insensitive to reversal (Zhou et al., 2003).”
Sleep and synaptic homeostasis: a hypothesis. (2003, result): “Alternatively, given that intense spontaneous activity can lead to the cleansing of uncorrelated synapses and to the relative consolidation of correlated ones [15,56], REM sleep could be achieving, with different means, an effect partly similar to the one postulated here for NREM sleep.”
Spike timing-dependent plasticity: from synapse to perception. (2006, methodology): “This modification was persistent after conditioning and involved NMDAR-dependent potentiation and depression of different subpopulations of retinotectal connections (122).”
Stable Learning in Stochastic Network States (2012, background): “This form of “spaced training” protocol has simple predictions that have been experimentally tested (Zhou et al., 2003; Dunfield and Haas, 2009).”
Sensitive Periods in the Development of the Brain and Behavior (2004, background): “In several systems, intense impulse activity, of the kind that can result from experience, has been shown to trigger gene transcription and translation and to activate existingmolecularcascadesforprocessesthatunderlieplasticity ( Zhou, Tao, & Poo, 2003; Kandel, 2001; Benson, Schnapp, Shapiro, & Hun”
Computational principles of synaptic memory consolidation (2016, background): “This implies that smaller nervous systems may do better with simpler synapses and larger nervous systems can benefit from more complex ones.”
Sleep and the Price of Plasticity: From Synaptic and Cellular Homeostasis to Memory Consolidation and Integration (2014, background): “An alternative possibility is suggested by the observation that intense spontaneous activity can lead to the cleansing of uncorrelated synapses and to the relative consolidation of correlated ones (Cohen-Cory, 2002; Zhou et al., 2003).”