These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
143 related articles for article (PubMed ID: 14511524)
1. Synaptic depression leads to nonmonotonic frequency dependence in the coincidence detector. Mikula S; Niebur E Neural Comput; 2003 Oct; 15(10):2339-58. PubMed ID: 14511524 [TBL] [Abstract][Full Text] [Related]
2. Correlated inhibitory and excitatory inputs to the coincidence detector: analytical solution. Mikula S; Niebur E IEEE Trans Neural Netw; 2004 Sep; 15(5):957-62. PubMed ID: 15484872 [TBL] [Abstract][Full Text] [Related]
3. Developmental changes in short-term synaptic depression in the neonatal mouse spinal cord. Li Y; Burke RE J Neurophysiol; 2002 Dec; 88(6):3218-31. PubMed ID: 12466442 [TBL] [Abstract][Full Text] [Related]
4. The information efficacy of a synapse. London M; Schreibman A; Häusser M; Larkum ME; Segev I Nat Neurosci; 2002 Apr; 5(4):332-40. PubMed ID: 11896396 [TBL] [Abstract][Full Text] [Related]
5. LTP regulates burst initiation and frequency at mossy fiber-granule cell synapses of rat cerebellum: experimental observations and theoretical predictions. Nieus T; Sola E; Mapelli J; Saftenku E; Rossi P; D'Angelo E J Neurophysiol; 2006 Feb; 95(2):686-99. PubMed ID: 16207782 [TBL] [Abstract][Full Text] [Related]
6. Including long-range dependence in integrate-and-fire models of the high interspike-interval variability of cortical neurons. Jackson BS Neural Comput; 2004 Oct; 16(10):2125-95. PubMed ID: 15333210 [TBL] [Abstract][Full Text] [Related]
7. Reducing the variability of neural responses: a computational theory of spike-timing-dependent plasticity. Bohte SM; Mozer MC Neural Comput; 2007 Feb; 19(2):371-403. PubMed ID: 17206869 [TBL] [Abstract][Full Text] [Related]
8. What can a neuron learn with spike-timing-dependent plasticity? Legenstein R; Naeger C; Maass W Neural Comput; 2005 Nov; 17(11):2337-82. PubMed ID: 16156932 [TBL] [Abstract][Full Text] [Related]
9. Pooled spike trains of correlated presynaptic inputs as realizations of cluster point processes. Gómez L; Budelli R; Saa R; Stiber M; Segundo JP Biol Cybern; 2005 Feb; 92(2):110-27. PubMed ID: 15688202 [TBL] [Abstract][Full Text] [Related]
10. Synaptic input statistics tune the variability and reproducibility of neuronal responses. Dorval AD; White JA Chaos; 2006 Jun; 16(2):026105. PubMed ID: 16822037 [TBL] [Abstract][Full Text] [Related]
12. Spiking neurons, dopamine, and plasticity: timing is everything, but concentration also matters. Thivierge JP; Rivest F; Monchi O Synapse; 2007 Jun; 61(6):375-90. PubMed ID: 17372980 [TBL] [Abstract][Full Text] [Related]
13. The firing of an excitable neuron in the presence of stochastic trains of strong synaptic inputs. Rubin J; Josić K Neural Comput; 2007 May; 19(5):1251-94. PubMed ID: 17381266 [TBL] [Abstract][Full Text] [Related]
14. Spike train statistics and dynamics with synaptic input from any renewal process: a population density approach. Ly C; Tranchina D Neural Comput; 2009 Feb; 21(2):360-96. PubMed ID: 19431264 [TBL] [Abstract][Full Text] [Related]
15. Depressed responses of facilitatory synapses. Banitt Y; Martin KA; Segev I J Neurophysiol; 2005 Jul; 94(1):865-70. PubMed ID: 15728769 [TBL] [Abstract][Full Text] [Related]