R. Silver

Cellular and Molecular Neuroscience · with Lorincz · 1992–2019

A researcher in the Science corpus: 11 papers; trusts 147 researchers and is trusted by 27 researchers here, as inferred from the citation graph.

Subfields

• Cellular and Molecular Neuroscience — 238 citations into it; #506 of 2,998 by trust here, #838 by citations
• Cognitive Neuroscience — 222 citations into it; #1,670 of 10,852 by trust here, #1,743 by citations
• Neurology — 109 citations into it; #221 of 1,455 by trust here, #270 by citations
• Sensory Systems — 95 citations into it
• Electrical and Electronic Engineering — 40 citations into it; #9,176 of 16,539 by trust here, #15,217 by citations
• Developmental Neuroscience — 25 citations into it
• Neuroscience — 24 citations into it; #315 of 487 by trust here, #466 by citations
• Genetics — 23 citations into it

Whom R. Silver trusts overall

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

1. D. Marr
2. Gilles Laurent
3. Henrik Jörntell
4. Glenn C. Turner
5. Rainer W. Friedrich
6. S. Brickley
7. L. F. Abbott
8. Barbara Olshausen
9. Peter Földiák
10. Masao Ito

Who trusts R. Silver overall

1. N. A. Cayco-Gajic
2. Henrik Jörntell
3. Guy O. Billings
4. Jeffery S. Isaacson
5. Liyuan Wang
6. Per Jesper Sjöström
7. A. Lorincz
8. Torben Ott
9. Chong Guo
10. Adam Kepecs

Papers from R. Silver's perspective

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

1. A theory of cerebellar cortex
2. A Theory of Cerebellar Function
3. Oscillations and Sparsening of Odor Representations in the Mushroom Body
4. Olfactory network dynamics and the coding of multidimensional signals
5. Pattern Separation in the Dentate Gyrus and CA3 of the Hippocampus
6. Olfactory representations by Drosophila mushroom body neurons.
7. Sparse coding of sensory inputs.
8. High-fidelity transmission of sensory information by single cerebellar mossy fibre boutons
9. Integration of quanta in cerebellar granule cells during sensory processing
10. Sparse Distributed Memory

Their papers

• Re-evaluating circuit mechanisms underlying pattern separation (2019) — 224 citations
• Gap Junctions Compensate for Sublinear Dendritic Integration in an Inhibitory Network (2012) — 122 citations
• Sparse synaptic connectivity is required for decorrelation and pattern separation in feedforward networks (2017) — 153 citations
• Functional Properties of Dendritic Gap Junctions in Cerebellar Golgi Cells (2016) — 58 citations
• Network Structure within the Cerebellar Input Layer Enables Lossless Sparse Encoding (2014) — 135 citations
• Neuronal arithmetic (2010) — 455 citations
• Synaptic depression enables neuronal gain control (2009) — 235 citations
• The Contribution of Single Synapses to Sensory Representation in Vivo (2008) — 196 citations
• Tonically active GABA A receptors: modulating gain and maintaining the tone. (2004) — 784 citations
• Shunting inhibition modulates neuronal gain during synaptic excitation. (2003) — 650 citations
• Rapid-time-course miniature and evoked excitatory currents at cerebellar synapses in situ (1992)