Rosalyn J. Moran

Cognitive Neuroscience · 2009–2013

A researcher in the Science corpus: 5 papers; trusts 23 researchers and is trusted by 21 researchers here, as inferred from the citation graph.

Subfields

• Cognitive Neuroscience — 97 citations into it; #1,586 of 10,852 by trust here, #2,173 by citations
• Cellular and Molecular Neuroscience — 27 citations into it
• Artificial Intelligence — 19 citations into it; #15,495 of 35,345 by trust here, #14,718 by citations
• Radiology, Nuclear Medicine and Imaging — 16 citations into it; #884 of 3,265 by trust here, #2,400 by citations
• Signal Processing — 13 citations into it
• Neuroscience — 8 citations into it
• Statistics and Probability — 7 citations into it; #5,638 of 12,932 by trust here, #3,330 by citations
• Neurology — 5 citations into it

Whom Rosalyn J. Moran trusts overall

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

1. Karl J. Friston
2. W. D. Penny
3. Klaas E. Stephan
4. Anil K. Seth
5. Jean Daunizeau
6. Stefan J. Kiebel
7. Clive W. J. Granger
8. Steven L. Bressler
9. Mingzhou Ding
10. Alard Roebroeck

Who trusts Rosalyn J. Moran overall

1. F. H. Lopes da Silva
2. Karl J. Friston
3. W. D. Penny
4. Jean Daunizeau
5. Hae-Jeong Park
6. Farzad Vasheghani Farahani
7. Karel Lebeda
8. Albert R. Powers
9. Klaas E. Stephan
10. C. Michel

Papers from Rosalyn J. Moran's perspective

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

1. Dynamic causal modelling
2. Variational free energy and the Laplace approximation
3. Nonlinear responses in fMRI: the Balloon model, Volterra kernels, and other hemodynamics. (NeuroImage)
4. Information Theory, Inference, and Learning Algorithms
5. Population dynamics: Variance and the sigmoid activation function
6. The Helmholtz Machine
7. Multiple sparse priors for the M/EEG inverse problem (NeuroImage)
8. Short-term synaptic plasticity.
9. Investigating directed cortical interactions in time-resolved fMRI data using vector autoregressive modeling and Granger causality mapping. (Magnetic Resonance Imaging)
10. The Bayesian brain: the role of uncertainty in neural coding and computation. (Trends in Neurosciences)

Their papers

• Bayesian Model Selection for Group Studies (2009) — 1,478 citations
• Analysing connectivity with Granger causality and dynamic causal modelling (2013) — 651 citations
• Dopamine, Affordance and Active Inference (2012) — 361 citations
• Ten Simple Rules for Dynamic Causal Modelling (2009) — 839 citations
• Dynamic causal modeling for EEG and MEG (2009) — 308 citations