Etienne Combrisson

Cognitive Neuroscience · 2015–2024

A researcher in the Science corpus: 4 papers; trusts 5 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Cognitive Neuroscience — 60 citations into it; #6,558 of 10,852 by trust here, #5,990 by citations
• Signal Processing — 5 citations into it

Whom Etienne Combrisson trusts overall

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

1. Thomas Schreiber
2. Olaf Sporns
3. Polina Golland
4. Clive W. J. Granger
5. William J. McGill
6. Johannes Lederer
7. Bruce Fischl
8. Richard S. Sutton
9. Michael Wibral
10. Partha P. Mitra

Who trusts Etienne Combrisson overall

1. Andrius Vabalas
2. Basile Pinsard
3. Emma Gowen
4. Olga Sourina
5. Arnaud Boutin
6. Ellen Poliakoff

Papers from Etienne Combrisson's perspective

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

1. Reinforcement Learning: An Introduction
2. Dynamic predictions: Oscillations and synchrony in top–down processing (Nature Reviews Neuroscience)
3. Hemodynamic Signals Correlate Tightly with Synchronized Gamma Oscillations (Science)
4. Measuring information transfer
5. A Neural Substrate of Prediction and Reward
6. The brainweb: Phase synchronization and large-scale integration (Nature Reviews Neuroscience)
7. Network attributes for segregation and integration in the human brain. (Current Opinion in Neurobiology)
8. Multivariate information transmission
9. Investigating causal relations by econometric models and cross-spectral methods
10. Rethinking segregation and integration: contributions of whole-brain modelling (Nature Reviews Neuroscience)

Their papers

• Neural interactions in the human frontal cortex dissociate reward and punishment learning (2024)
• Group-level inference of information-based measures for the analyses of cognitive brain networks from neurophysiological data (2021)
• From intentions to actions: Neural oscillations encode motor processes through phase, amplitude and phase‐amplitude coupling (2017)
• Exceeding chance level by chance: The caveat of theoretical chance levels in brain signal classification and statistical assessment of decoding accuracy. (2015) — 607 citations