Joshua W. Brown
Cognitive Neuroscience · Science · 2002–2019
A researcher in the Science corpus: 10 papers; trusts 30 researchers and is trusted by 51 researchers here, as inferred from the citation graph.
Subfields
- Cognitive Neuroscience — 93 citations into it; #534 of 10,852 by trust here, #1,021 by citations
- Neuroscience — 14 citations into it
- Reinforcement Learning — 13 citations into it
- Artificial Intelligence — 12 citations into it; #28,222 of 35,345 by trust here, #27,551 by citations
- Cellular and Molecular Neuroscience — 11 citations into it
- Statistics and Probability — 6 citations into it
- Cognitive Science & Psychology — 5 citations into it
Whom Joshua W. Brown trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Matthew Botvinick
- Andrew Barto
- J. Cohen
- Todd S. Braver
- Roger Ratcliff
- A. Harry Klopf
- Leslie Pack Kaelbling
- Clay B. Holroyd
- Peter S. Dayan
- Thomas Goschke
Who trusts Joshua W. Brown overall
- Matthew Botvinick
- Amitai Shenhav
- Markus Ullsperger
- Srikanth Padmala
- Krishna D. Singh
- Luiz Pessoa
- René Martin
- Thérèse J. M. Overbeek
- Frederick Verbruggen
- J. Cohen
Papers from Joshua W. Brown's perspective
Ordered by how strongly the researchers Joshua W. Brown trusts endorse each paper. Same corpus, a different order for every researcher.
- Reinforcement Learning: An Introduction
- Long Short-Term Memory
- Conflict monitoring and cognitive control. (Psychology Review)
- Reinforcement Learning: A Survey
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- The neural basis of human error processing: reinforcement learning, dopamine, and the error-related negativity. (Psychology Review)
- Parsing executive processes: strategic vs. evaluative functions of the anterior cingulate cortex. (Proceedings of the National Academy of Sciences of the United States of America)
- Learning internal representations by error propagation
- ImageNet classification with deep convolutional neural networks
- Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
Their papers
- A consensus guide to capturing the ability to inhibit actions and impulsive behaviors in the stop-signal task (2019) — 741 citations
- Hierarchical Error Representation: A Computational Model of Anterior Cingulate and Dorsolateral Prefrontal Cortex (2015) — 103 citations
- Prefrontal cortex organization: dissociating effects of temporal abstraction, relational abstraction, and integration with FMRI. (2014)
- Dissociable frontal-striatal and frontal-parietal networks involved in updating hierarchical contexts in working memory. (2013)
- Rostral-Caudal Gradients of Abstraction Revealed by Multi-Variate Pattern Analysis of Working Memory (2012)
- Medial prefrontal cortex as an action-outcome predictor (2011) — 924 citations
- A computational model of fractionated conflict-control mechanisms in task-switching. (2007) — 207 citations
- Learned Predictions of Error Likelihood in the Anterior Cingulate Cortex (2005) — 963 citations
- Performance Monitoring by the Anterior Cingulate Cortex During Saccade Countermanding (2003) — 616 citations
- Computational perspectives on dopamine function in prefrontal cortex. (2002) — 402 citations