Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Conflict monitoring and cognitive control.
20015.3k citationsMatthew Botvinick, Jonathan D. Cohen et al.profile →
Conflict monitoring and anterior cingulate cortex: an update
20042.8k citationsMatthew Botvinick, Jonathan D. Cohen et al.Trends in Cognitive Sciencesprofile →
Anterior Cingulate Cortex, Error Detection, and the Online Monitoring of Performance
19982.6k citationsMatthew Botvinick, Jonathan D. Cohen et al.Scienceprofile →
Conflict monitoring versus selection-for-action in anterior cingulate cortex
19991.6k citationsMatthew Botvinick et al.profile →
The Neural Basis of Error Detection: Conflict Monitoring and the Error-Related Negativity.
20041.5k citationsMatthew Botvinick, Jonathan D. Cohen et al.profile →
The Expected Value of Control: An Integrative Theory of Anterior Cingulate Cortex Function
20131.5k citationsAmitai Shenhav, Matthew Botvinick et al.profile →
Machine learning classifiers and fMRI: A tutorial overview
20081.2k citationsMatthew Botvinick et al.profile →
Countries citing papers authored by Matthew Botvinick
Since
Specialization
Citations
This map shows the geographic impact of Matthew Botvinick's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Matthew Botvinick with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew Botvinick more than expected).
Fields of papers citing papers by Matthew Botvinick
This network shows the impact of papers produced by Matthew Botvinick. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Matthew Botvinick. The network helps show where Matthew Botvinick may publish in the future.
Co-authorship network of co-authors of Matthew Botvinick
This figure shows the co-authorship network connecting the top 25 collaborators of Matthew Botvinick.
A scholar is included among the top collaborators of Matthew Botvinick based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Matthew Botvinick. Matthew Botvinick is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Hill, Felix, Andrew K. Lampinen, Rosalia Schneider, et al.. (2020). Environmental drivers of systematicity and generalization in a situated agent.. International Conference on Learning Representations.9 indexed citations
8.
Song, Hao, Abbas Abdolmaleki, Jost Tobias Springenberg, et al.. (2020). V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control. arXiv (Cornell University).3 indexed citations
9.
Goyal, Anirudh, Riashat Islam, Zafarali Ahmed, et al.. (2019). InfoBot: Transfer and Exploration via the Information Bottleneck. arXiv (Cornell University).8 indexed citations
Tacchetti, Andrea, Hui Song, Pedro A. M. Mediano, et al.. (2018). Relational Forward Models for Multi-Agent Learning. UCL Discovery (University College London).7 indexed citations
13.
Higgins, Irina, Nicolas Sonnerat, Löıc Matthey, et al.. (2018). SCAN: Learning Hierarchical Compositional Visual Concepts. UCL Discovery (University College London).17 indexed citations
14.
Morcos, Ari S., David G. T. Barrett, Neil C. Rabinowitz, & Matthew Botvinick. (2018). On the importance of single directions for generalization. arXiv (Cornell University).15 indexed citations
Botvinick, Matthew, et al.. (2010). Learning semantic features for fMRI data from definitional text. North American Chapter of the Association for Computational Linguistics. 1–9.10 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.