Activity-dependent scaling of quantal amplitude in neocortical neurons

By Gina G. Turrigiano, K. R. Leslie, Niraj S. Desai, L. C. Rutherford, Sacha B. Nelson. 1998

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Citations in the corpus

The temporal paradox of Hebbian learning and homeostatic plasticity (2017, background): “ology, forms of plasticity exist which seemingly enforce such limits or constraints through synaptic scaling in response to firing rate perturbations [13, 14], or through stabilizing adjustments of the properties of plasticity in response to the recent synaptic history, a phenomenon known as”
Intrinsic Stabilization of Output Rates by Spike-Based Hebbian Learning (2001, background): “Turrigiano et al. (1998) suggest that rate normalization is achieved by multiplying all weights by the same factor.”
Activity-dependent structural plasticity. (2009, background): “In all these cases presented, functional plasticity in terms of changes in synaptic efficacies (Heynen et al., 2003), including synaptic scaling (Turrigiano et al., 1998), of existing synapses may not be sufficient to rebalance neuronal activities.”
Inactivity produces increases in neurotransmitter release and synapse size. (2001, background): “(Turrigiano et al., 1998; Watt et al. ,”
A History of Spike-Timing-Dependent Plasticity (2011, background): “…rules seems key to future progress in our understanding of the relationship between intrinsically unstable synaptic plasticity and stability-promoting mechanisms such as synaptic scaling (Turrigiano et al., 1998; Turrigiano and Nelson, 2000; Izhikevich and Desai, 2003; Watt and Desai, 2010).”
How does Nature Program Neuron Types? (2008, result): “Along similar lines, the work of Turrgiano, Nelson and colleagues (Turrigiano et al, 1998) has shown that synaptic strength is another parameter that is regulated such as to remain in an operating range appropriate to neuronal function.”
Receptive field formation by interacting excitatory and inhibitory synaptic plasticity (2016, background): “Multiplicative normalization scales all weights such that the sum of the squared weights is held constant, a mechanism that could be implemented by homeostatic synaptic scaling (Turrigiano et al., 1998).”
Protein palmitoylation in neuronal development and synaptic plasticity (2010, background): “It is well established that the prolonged blockade (24–48 hours) of synaptic activity increases synaptic strength by recruiting additional AMPARs to synapses to normalize inputs and stabilize neuronal circuits; this process is known as synaptic up-scalin”
Rapid homeostasis by disinhibition during whisker map plasticity (2014, background): “This finding is consistent with prior results (24) and not consistent with global homeostasis mediated by synaptic scaling (2, 13).”
Astrocyte roles in traumatic brain injury (2015, background): “…of homeostatic synaptic plasticity, tunes global excitatory synaptic strength to fluctuations in firing rate by increasing postsynaptic α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) density across all of a neurons’ synapses (Turrigiano et al., 1998; Beattie et al., 2002).”
Homeostatic plasticity in the developing nervous system (2004, background): “The reciprocal manipulation — elevating network activity by reducing a fraction of inhibition — initially raises firing rates, but over many hours firing rates fall again until they approach control level”
Stable Hebbian Learning from Spike Timing-Dependent Plasticity (2000, methodology): “As in our model, the shape of the distributions of both quantal amplitudes (Turrigiano et al., 1998; O’Brien et al., 1998) and of receptor staining (O’Brien et al., 1998) is preserved when synaptic strengths are scaled up or down in response to changes in activity.”
Neuromorphic Electronic Circuits for Building Autonomous Cognitive Systems (2014, result): “In [67] the authors demonstrate that this sub-circuit is functionally equivalent to the one described in theoretical models, and often used in computational neuroscience simulations [72], [73].”