Synaptic Depression and Cortical Gain Control

By L. F. Abbott, J. A. Varela, Kamal Sen, Sacha B. Nelson. 1997

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Citations in the corpus

Normalization as a canonical neural computation (2011, background): “In particular, a mechanism that could provide the appropriate non-linearity is synaptic depressio”
A Synaptic Explanation of Suppression in Visual Cortex (2002, background): “The time constant of recovery was R 200 msec, intermediate between those reported for rapid depression in young animals (200–800 msec) (Abbott et al., 1997; Varela et al., 1997) and in adult animals (60–70 msec) (Thomson and Deuchars, 1997).”
Short-term presynaptic plasticity. (2012, background): “In this way, a depressing synaptic connection responds transiently to changes in firing rate in a way that encodes percentage changes in firing rate (Abbott et al. 1997).”
Somatosensory integration controlled by dynamic thalamocortical feed-forward inhibition. (2005, unknown): “crease in resource (such as vesicles) available after each spike followed by recovery with an exponential time constant (Abbott et al., 1997; Tsodyks and Markram, 1997).”
Impact of active dendrites and structural plasticity on the memory capacity of neural tissue. (2001, result): “based on the recent activation history of the synapse, In a departure from the common view that memories the straightforward mapping of stable numerical weights are encoded in the overall connection strengths befrom a connectionist learning system onto synapses in tween neurons, our results suggest ”
Neural Networks with Dynamic Synapses (1998, methodology): “The phenomenological formulation of Tsodyks and Markram (1996) and Abbott et al. (1997) can be generalized to describe facilitating synapses be-”
Action and behavior: a free-energy formulation (2010, background): “In a perceptual setting, they may mediate attentional gain (cf., Abbott et al. 1997; Yu and Dayan 2005; Friston 2008).”
An Organic Nanoparticle Transistor Behaving as a Biological Spiking Synapse (2009, background): “ G. Le Masson, S. Renaud-Le Masson, D. Debay, T. Bal, Nature 2002, 417, 854. [4] http://facets.kip.uni-heidelberg.de, 2005. [5] M. Boegerhausen, P. Suter, S.-C. Liu, Neural Computation 2003, 15, 331. [6] J. Borghetti, V. Derycke, S. Lenfant, P. Chenevier, A. Filoramo, M. Goffman, D. Vuillaume, J. P.”
A Normalization Model of Multisensory Integration (2011, unknown): “This input non-linearity models response saturation in the sensory inputs 21 , which could be mediated via synaptic depression 22 or normalization within the unisensory pathways.”
Suppression without inhibition in visual cortex. (2002, background): “…followed a similar 20 ms delay, at the low end of published esti-1997; Varela et al., 1997), shorter than the 1–2 s interval between our adapting stimuli and the subsequent probe mates for the time constant of recovery from synaptic depression (Abbott et al., 1997; Thomson and Deuchars,stimuli.”
Neural processing of amplitude-modulated sounds. (2004, background): “s(t) [1 m sin (2 fmt)] sin (2 fct) (1)”