Graded bidirectional synaptic plasticity is composed of switch-like unitary events.

By Daniel H. O’Connor, G. M. Wittenberg, S. Wang. 2005

259 citations recorded by the source corpus.

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

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cellular and Molecular Neuroscience

In Cognitive Neuroscience

In Electrical and Electronic Engineering

Citations in the corpus

Subdominant Dense Clusters Allow for Simple Learning and High Computational Performance in Neural Networks with Discrete Synapses. (2015, methodology): “[6] Yann LeCun, Léon Bottou, Yoshua Bengio, and Patrick Haffner.”
A memory frontier for complex synapses (2013, background): “However, recent experimental work has shown that many synapses are more digital than analog; they cannot robustly assume an infinite continuum of analog values, but rather can only take on a finite number of distinguishable strengths, a number than can be as small as two [4–6] (though see [7]).”
Constraint satisfaction problems and neural networks: A statistical physics perspective. (2008, background): “However, recent experimental studies have shown that some synapses undergo changes in the form of jumps between a ﬁnite number of stable states (Petersen et al., 1998; O’Connor et al., 2005).”
Statistical mechanics of complex neural systems and high dimensional data (2013, background): “) in ﬁnite time for analog synaptic weights. However, what if synaptic weights cannot take arbitrary analog values? Indeed evidence suggests that biological synapses behave like noisy binary switches [88, 89], and thus can reliably code only two levels of synaptic weights, rather than a continuum. T”
Synaptic Consolidation: From Synapses to Behavioral Modeling (2015, background): “First, minimal LTP stimulation protocols indicate that changes in the amplitude of the postsynaptic current (PSC) or postsynaptic potential (PSP) are visible already a few seconds after the induction protocol (Petersen et al., 1998; O’Connor et al., 2005).”
State Based Model of Long-Term Potentiation and Synaptic Tagging and Capture (2009, methodology): “This rapid switching is motivated by the abovementioned observations at the single synapse level [ 22 ], and is assumed to come about from AMPA receptor insertion.”
Neural mechanism for stochastic behaviour during a competitive game (2006, background): “in generating a random sequence of choices (Bar-Hillel & Wagenaar, 1991; Camerer, 2003), but with feedback they can learn to generate sequences that can pass standard randomness tests ( Neuringer, 1986 ).”
Sparseness constrains the prolongation of memory lifetime via synaptic metaplasticity. (2008, background): “Two remarkable discoveries are all-or-none potentiation anddepression (Petersen et al. 1998;O’Connor et al. 2005) and silent synapses (Isaac et al. 1995; Liao et al. 1995; Montgomery et al. 2001).”
Does Spike-Timing-Dependent Synaptic Plasticity Couple or Decouple Neurons Firing in Synchrony? (2012, background): “There is actually another implicit assumption (made by virtually all STDP models) that all spike pairings would contribute linearly to weight change on the short time scale of plasticity induction, whereas there is evidence that the initial phase of LTP or LTD is highly non-linear involving transiti”
Phenomenological models of synaptic plasticity based on spike timing (2008, background): “At a first glance, this seems to be at odds with experimental data suggesting that single synaptic contacts are in fact binary (Petersen et al. 1998; O’Connor et al. 2005).”
Critical period plasticity in local cortical circuits (2005, background): “Excessive emphasis on LTP/LTD alone (which is all-or-none at single synapse”