AMPARs and synaptic plasticity: the last 25 years.
By Richard L. Huganir, R. Nicoll. Neuron, 2013
900 citations recorded by the source corpus.
Subfields: Cellular and Molecular Neuroscience, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/7bcce9d1b71f516bd6cca99748c376434e65e6b5
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Cellular and Molecular Neuroscience
- Wulfram Gerstner
- Johanni Brea
- Dane S. Corneil
- Vasiliki Liakoni
- Marco P Lehmann
- Taro Toyoizumi
- Kenneth D. Miller
- Michael P. Stryker
In Electrical and Electronic Engineering
- Wulfram Gerstner
- Johanni Brea
- Dane S. Corneil
- Vasiliki Liakoni
- Marco P Lehmann
- Taro Toyoizumi
- Kenneth D. Miller
- Michael P. Stryker
Citations in the corpus
- Eligibility Traces and Plasticity on Behavioral Time Scales: Experimental Support of NeoHebbian Three-Factor Learning Rules (2018, background): “Synapses contain complex molecular machineries (Lisman, 2003, 2017; Redondo and Morris, 2011; Huganir and Nicoll, 2013), but for the sake of transparency of the arguments, we will keep the mathematical notation as simple as possible and characterize the synapse by two variables only: the first one i”
- Modeling the dynamic interaction of Hebbian and homeostatic plasticity. (2014, positive): “These slots are created by PSD structural proteins (Huganir and Nicoll, 2013; Kessels and Malinow, 2009), some of which play roles in homeostatic plasticity (Shin et al., 2012; Steinmetz and Turrigiano, 2010; Sun and Turrigiano, 2011).”