Guy O. Billings

Cognitive Neuroscience · 2009–2014

A researcher in the Science corpus: 4 papers; trusts 17 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Cognitive Neuroscience — 53 citations into it; #7,023 of 10,852 by trust here, #5,162 by citations
• Cellular and Molecular Neuroscience — 52 citations into it; #1,805 of 2,998 by trust here, #1,976 by citations
• Electrical and Electronic Engineering — 28 citations into it
• Neuroscience — 12 citations into it

Whom Guy O. Billings trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Sen Song
2. Abigail Morrison
3. Misha Tsodyks
4. L. F. Abbott
5. Eugene M. Izhikevich
6. William E. Vinje
7. Robert Froemke
8. Wulfram Gerstner
9. D. Marr
10. R. Silver

Who trusts Guy O. Billings overall

1. Stefano Fusi
2. Friedemann Zenke
3. Wulfram Gerstner
4. Pierre Yger
5. Pascal Leimer
6. A. Govindarajan

Papers from Guy O. Billings's perspective

Ordered by how strongly the researchers Guy O. Billings trusts endorse each paper. Same corpus, a different order for every researcher.

1. Competitive Hebbian learning through spike-timing-dependent synaptic plasticity
2. Regulation of Synaptic Efficacy by Coincidence of Postsynaptic APs and EPSPs
3. A theory of cerebellar cortex
4. Temporal contiguity requirements for long-term associative potentiation/depression in the hippocampus.
5. An Algorithm for Modifying Neurotransmitter Release Probability Based on Pre- and Postsynaptic Spike Timing
6. Activity-dependent scaling of quantal amplitude in neocortical neurons
7. Hebbian learning and spiking neurons
8. A unified model of NMDA receptor-dependent bidirectional synaptic plasticity (Proceedings of the National Academy of Sciences of the United States of America)
9. Synaptic plasticity: taming the beast
10. A Theory of Cerebellar Function

Their papers

• Memory retention and spike-timing-dependent plasticity. (2009) — 78 citations
• NeuroML: A Language for Describing Data Driven Models of Neurons and Networks with a High Degree of Biological Detail (2010) — 334 citations
• Network Structure within the Cerebellar Input Layer Enables Lossless Sparse Encoding (2014) — 135 citations
• State Based Model of Long-Term Potentiation and Synaptic Tagging and Capture (2009) — 93 citations