Theory of Cortical Plasticity

By Leon N. Cooper, N. Intrator, B. Blais, Harel Z. Shouval. 2004

129 citations recorded by the source corpus.

How researchers see this paper

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The temporal paradox of Hebbian learning and homeostatic plasticity (2017, background): “(a) Unstable oscillations in the BCM model for a simple feed-forward circuit [6, 11].”
Frontiers in Synaptic Neuroscience Synaptic Neuroscience (unknown): “mappIng Stdp onto Bcm Since its introduction, the BCM rule has been widely used to model brain processes related to learning and experience-dependent development (Bear, 2003; Cooper et al., 2004; Abraham, 2008).”
Modeling the dynamic interaction of Hebbian and homeostatic plasticity. (2014, methodology): “Instability occurs when the threshold change is so slow that the threshold never catches up (Cooper et al., 2004; Zenke et al., 2013) (when tq=tw>1=ðx2y0Þ for Equations 1 and 2).”
Models of Metaplasticity: A Review of Concepts (2015, methodology): “It is known that the BCM formalism can be subject to strong oscillations, when the timescales for the two differential equations are too far apart (Cooper et al., 2004; Toyoizumi et al., 2014).”
Triplets of Spikes in a Model of Spike Timing-Dependent Plasticity (2006, background): “Note that the objective function exists only if we assume that (cid:10) is a function of (cid:14) (cid:8) (cid:15) and not (cid:14) (cid:8) y (cid:15) p (See also Cooper et al., 2004).”
Synaptic Plasticity in Neural Networks Needs Homeostasis with a Fast Rate Detector (2013, unknown): “The BCM theory relies on a plasticity rule with a neuron wide sliding threshold [15,51].”