@article {1364586,
	title = {Depression-biased reverse plasticity rule is required for stable learning at top-down connections},
	journal = {PLoS Comput Biol},
	volume = {8},
	number = {3},
	year = {2012},
	month = {2012},
	pages = {e1002393},
	abstract = {Top-down synapses are ubiquitous throughout neocortex and play a central role in cognition, yet little is known about their development and specificity. During sensory experience, lower neocortical areas are activated before higher ones, causing top-down synapses to experience a preponderance of post-synaptic activity preceding pre-synaptic activity. This timing pattern is the opposite of that experienced by bottom-up synapses, which suggests that different versions of spike-timing dependent synaptic plasticity (STDP) rules may be required at top-down synapses. We consider a two-layer neural network model and investigate which STDP rules can lead to a distribution of top-down synaptic weights that is stable, diverse and avoids strong loops. We introduce a temporally reversed rule (rSTDP) where top-down synapses are potentiated if post-synaptic activity precedes pre-synaptic activity. Combining analytical work and integrate-and-fire simulations, we show that only depression-biased rSTDP (and not classical STDP) produces stable and diverse top-down weights. The conclusions did not change upon addition of homeostatic mechanisms, multiplicative STDP rules or weak external input to the top neurons. Our prediction for rSTDP at top-down synapses, which are distally located, is supported by recent neurophysiological evidence showing the existence of temporally reversed STDP in synapses that are distal to the post-synaptic cell body.},
	keywords = {Action Potentials, Computer Simulation, Humans, Long-Term Synaptic Depression, Models, Neurological, Neocortex, Nerve Net, Neural Inhibition, Neuronal Plasticity, Neurons, Synaptic Transmission},
	issn = {1553-7358},
	doi = {10.1371/journal.pcbi.1002393},
	author = {Burbank, Kendra S and Kreiman, Gabriel}
}
