Robert Gütig
Cognitive Neuroscience · 2003–2006
A researcher in the Science corpus: 2 papers; trusts 14 researchers and is trusted by 25 researchers here, as inferred from the citation graph.
Subfields
- Cognitive Neuroscience — 22 citations into it; #1,187 of 10,852 by trust here, #2,252 by citations
- Cellular and Molecular Neuroscience — 21 citations into it; #266 of 2,998 by trust here, #705 by citations
- Electrical and Electronic Engineering — 15 citations into it; #1,123 of 16,539 by trust here, #4,543 by citations
- Neuroscience — 8 citations into it
Whom Robert Gütig trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Richard Kempter
- H. Sebastian Seung
- John E. Lisman
- Guoqiang Bi
- Sen Song
- Wulfram Gerstner
- Kenneth D. Miller
- Dean V. Buonomano
- Jonathan E. Rubin
- L. F. Abbott
Who trusts Robert Gütig overall
- Friedemann Zenke
- Hesham Mostafa
- Robert Froemke
- Matthieu Gilson
- Pierre Yger
- David P. Reichert
- Joseph M. Brader
- Elisabetta Chicca
- Yotam Luz
- Wei Fang
Papers from Robert Gütig's perspective
Ordered by how strongly the researchers Robert Gütig trusts endorse each paper. Same corpus, a different order for every researcher.
- Regulation of Synaptic Efficacy by Coincidence of Postsynaptic APs and EPSPs
- Synaptic Modifications in Cultured Hippocampal Neurons: Dependence on Spike Timing, Synaptic Strength, and Postsynaptic Cell Type
- Temporal contiguity requirements for long-term associative potentiation/depression in the hippocampus.
- Synaptic plasticity: taming the beast
- Timing-based LTP and LTD at vertical inputs to layer II/III pyramidal cells in rat barrel cortex. (Neuron)
- A neuronal learning rule for sub-millisecond temporal coding
- An Algorithm for Modifying Neurotransmitter Release Probability Based on Pre- and Postsynaptic Spike Timing
- Introduction to the theory of neural computation
- Learning in spiking neural networks by reinforcement of stochastic synaptic transmission.
- Optimal information storage and the distribution of synaptic weights: perceptron versus Purkinje cell.
Their papers
- The tempotron: a neuron that learns spike timing–based decisions (2006) — 844 citations
- Learning Input Correlations through Nonlinear Temporally Asymmetric Hebbian Plasticity (2003) — 424 citations