caa a22 4500 463244869 CHVBK 20180405153322.0 cr unu---uuuuu 170326e20070701xx s 000 0 eng 10.1007/s00422-007-0155-3 doi (NATIONALLICENCE)springer-10.1007/s00422-007-0155-3 Kinetic models of spike-timing dependent plasticity and their functional consequences in detecting correlations [Elektronische Daten] [Quan Zou, Alain Destexhe] Spike-timing dependent plasticity (STDP) is a type of synaptic modification found relatively recently, but the underlying biophysical mechanisms are still unclear. Several models of STDP have been proposed, and differ by their implementation, and in particular how synaptic weights saturate to their minimal and maximal values. We analyze here kinetic models of transmitter-receptor interaction and derive a series of STDP models. In general, such kinetic models predict progressive saturation of the weights. Various forms can be obtained depending on the hypotheses made in the kinetic model, and these include a simple linear dependence on the value of the weight ("soft bounds”), mixed soft and abrupt saturation ("hard bound”), or more complex forms. We analyze in more detail simple soft-bound models of Hebbian and anti-Hebbian STDPs, in which nonlinear spike interactions (triplets) are taken into account. We show that Hebbian STDPs can be used to selectively potentiate synapses that are correlated in time, while anti-Hebbian STDPs depress correlated synapses, despite the presence of nonlinear spike interactions. This correlation detection enables neurons to develop a selectivity to correlated inputs. We also examine different versions of kinetics-based STDP models and compare their sensitivity to correlations. We conclude that kinetic models generally predict soft-bound dynamics, and that such models seem ideal for detecting correlations among large numbers of inputs. Springer-Verlag, 2007 STDP nationallicence Synaptic plasticity nationallicence Computational models nationallicence Biophysical models nationallicence Zou Quan Integrative and Computational Neuroscience Unit (UNIC), CNRS, 1 Avenue de la Terrasse, 91198, Gif-sur-Yvette, France aut Destexhe Alain Integrative and Computational Neuroscience Unit (UNIC), CNRS, 1 Avenue de la Terrasse, 91198, Gif-sur-Yvette, France aut Biological Cybernetics Springer-Verlag 97/1(2007-07-01), 81-97 0340-1200 97:1<81 2007 97 422 https://doi.org/10.1007/s00422-007-0155-3 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s00422-007-0155-3 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Zou Quan Integrative and Computational Neuroscience Unit (UNIC), CNRS, 1 Avenue de la Terrasse, 91198, Gif-sur-Yvette, France aut NATIONALLICENCE 700 1- Destexhe Alain Integrative and Computational Neuroscience Unit (UNIC), CNRS, 1 Avenue de la Terrasse, 91198, Gif-sur-Yvette, France aut NATIONALLICENCE 773 0- Biological Cybernetics Springer-Verlag 97/1(2007-07-01), 81-97 0340-1200 97:1<81 2007 97 422 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer