title: A theory of loop formation and elimination by spike timing-dependent plasticity.
abstract: We show that the local spike timing-dependent plasticity (STDP) rule has the effect of regulating the trans-synaptic weights of loops of any length within a simulated network of neurons. We show that depending on STDP's polarity, functional loops are formed or eliminated in networks driven to normal spiking conditions by random, partially correlated inputs, where functional loops comprise synaptic weights that exceed a positive threshold. We further prove that STDP is a form of loop-regulating plasticity for the case of a linear network driven by noise. Thus a notable local synaptic learning rule makes a specific prediction about synapses in the brain in which standard STDP is present: that under normal spiking conditions, they should participate in predominantly feed-forward connections at all scales. Our model implies that any deviations from this prediction would require a substantial modification to the hypothesized role for standard STDP. Given its widespread occurrence in the brain, we predict that STDP could also regulate long range functional loops among individual neurons across all brain scales, up to, and including, the scale of global brain network topology.
authors.affiliation: Biometaphorical Computing, Computational Biology Center, IBM Research Division, IBM T. J. Watson Research Center Yorktown Heights, NY, USA.
authors.forename: James
authors.initials: J
authors.lastname: Kozloski
authors.forename: Guillermo A
authors.initials: GA
authors.lastname: Cecchi
references.citation: Nat Neurosci. 2000 Nov;3 Suppl:1178-83
references.pmid: 11127835
references.citation: Cereb Cortex. 2008 Jan;18(1):13-28
references.pmid: 17420172
references.citation: Proc Natl Acad Sci U S A. 2006 Aug 29;103(35):13214-9
references.pmid: 16924105
references.citation: Biol Cybern. 2008 Jun;98(6):459-78
references.pmid: 18491160
references.citation: PLoS Biol. 2005 Mar;3(3):e68
references.pmid: 15737062
references.citation: J Neurosci. 2005 Dec 7;25(49):11279-87
references.pmid: 16339023
references.citation: J Physiol. 2008 Jan 1;586(1):265-82
references.pmid: 17974593
references.citation: Neural Comput. 2004 May;16(5):885-940
references.pmid: 15070504
references.citation: Science. 1997 Jan 10;275(5297):213-5
references.pmid: 8985014
references.citation: Nature. 1998 Jan 15;391(6664):245-50
references.pmid: 9440687
references.citation: J Neurosci. 2003 May 1;23(9):3697-714
references.pmid: 12736341
references.citation: Nat Neurosci. 2000 Sep;3(9):919-26
references.pmid: 10966623
references.citation: J Neurosci. 2008 Aug 6;28(32):7968-78
references.pmid: 18685022
references.citation: Proc Natl Acad Sci U S A. 2008 Dec 9;105(49):19235-40
references.pmid: 19033453
references.citation: Neuron. 2007 Sep 20;55(6):919-29
references.pmid: 17880895
references.citation: J Neurosci. 2008 Mar 5;28(10):2435-46
references.pmid: 18322089
references.citation: Neural Comput. 2008 Feb;20(2):415-35
references.pmid: 18045011