Maurice A. Smith

Cognitive Neuroscience · 2006–2014

A researcher in the Science corpus: 3 papers; trusts 5 researchers and is trusted by 19 researchers here, as inferred from the citation graph.

Subfields

• Cognitive Neuroscience — 35 citations into it; #1,830 of 10,852 by trust here, #4,170 by citations
• Social Psychology — 15 citations into it; #4,205 of 15,694 by trust here, #8,798 by citations
• Biomedical Engineering — 8 citations into it; #2,448 of 10,734 by trust here, #6,312 by citations
• Cellular and Molecular Neuroscience — 5 citations into it

Whom Maurice A. Smith trusts overall

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

1. Reza Shadmehr
2. Ferdinando A. Mussa-Ivaldi
3. Stefano Fusi
4. David J. Reinkensmeyer
5. John W. Krakauer
6. J. Saunders

Who trusts Maurice A. Smith overall

1. Jordan A. Taylor
2. D. M. Wolpert
3. John W. Krakauer
4. Samuel David McDougle
5. Gregory Hickok
6. Reza Shadmehr
7. Jörn Diedrichsen
8. Richard B. Ivry
9. Giovanni Pezzulo
10. Jeffrey S. Bowers

Papers from Maurice A. Smith's perspective

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

1. Humans integrate visual and haptic information in a statistically optimal fashion (Nature)
2. Motor learning by field approximation.
3. Motion illusions as optimal percepts (Nature Neuroscience)
4. Learning to move amid uncertainty. (Journal of Neurophysiology)
5. Humans use continuous visual feedback from the hand to control fast reaching movements
6. Efficiency and ambiguity in an adaptive neural code (Nature)
7. A computational neuroanatomy for motor control
8. Motor Adaptation as a Process of Reoptimization (Journal of Neuroscience)
9. One Hundred Years of Forgetting : A Quantitative Description of Retention
10. Motor Task Variation Induces Structural Learning

Their papers

• Error correction, sensory prediction, and adaptation in motor control. (2010) — 1,725 citations
• Interacting Adaptive Processes with Different Timescales Underlie Short-Term Motor Learning (2006) — 1,130 citations
• Temporal structure of motor variability is dynamically regulated and predicts motor learning ability (2014) — 629 citations