Adaptive Cognitive Systems

21.7k citations
278 papers ·

Impact in

    • Neural dynamics and brain function
    • Visual perception and processing mechanisms
    • Memory and Neural Mechanisms
    • Neural and Behavioral Psychology Studies
    • Neural Networks and Applications

Papers in

Adaptive Cognitive Systems

265 papers receiving 21.3k citations

Peers

Adaptive Cognitive Systems
Comparison fields: 5 of 195
  • Cognitive Neuroscience 12.6k
  • Artificial Intelligence 5.5k
  • Computer Vision and Pattern Recognition 3.4k
  • Experimental and Cognitive Psychology 1.8k
  • Cellular and Molecular Neuroscience 1.9k
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Sage Bionetworks United States
MicroVision (United States) United States
Silicon Valley Community Foundation United States
Machine Intelligence Research Institute United States
USC Institute for Creative Technologies United States
Art Institute of Portland United States
Snap (United States) United States
New York Institute of Technology Canada
Telus (Canada) Canada
Owl Research Institute United States
Adaptive Cognitive Systems relative to Sage Bionetworks United States Sage Bionetworks's profile →
Citations per field
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Citations per year

Countries citing scholars working at Adaptive Cognitive Systems

Since Specialization
Citations

This map shows the geographic impact of research produced by authors working at Adaptive Cognitive Systems. 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 papers produced at Adaptive Cognitive Systems with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Adaptive Cognitive Systems more than expected).

Fields of papers published by authors at Adaptive Cognitive Systems

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers affiliated with Adaptive Cognitive Systems at the time of their publication. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers affiliated with Adaptive Cognitive Systems at the time of their publication.

About Adaptive Cognitive Systems

In recent decades, authors affiliated with Adaptive Cognitive Systems have published 278 papers, which have received a total of 21.7k indexed citations . Scholars at this organization have produced 221 papers in Cognitive Neuroscience, 43 papers in Computer Vision and Pattern Recognition, 35 papers in Cellular and Molecular Neuroscience, 62 papers in Artificial Intelligence and 10 papers in Neurology on the topics of Neural dynamics and brain function (129 papers), Visual perception and processing mechanisms (113 papers), Neural Networks and Applications (49 papers), Memory and Neural Mechanisms (35 papers), Neuroscience and Neuropharmacology Research (21 papers), Color Science and Applications (21 papers), Advanced Vision and Imaging (19 papers) and Neural and Behavioral Psychology Studies (16 papers). Their work is cited by papers focused on Cognitive Neuroscience (12.6k citations), Artificial Intelligence (5.5k citations), Computer Vision and Pattern Recognition (3.4k citations), Experimental and Cognitive Psychology (1.8k citations) and Cellular and Molecular Neuroscience (1.9k citations). Authors at Adaptive Cognitive Systems collaborate with scholars in United States, Germany and Italy and have published in prestigious journals including Neural Networks, Vision Research, Biological Cybernetics, Psychological Review and Journal of Vision. Some of Adaptive Cognitive Systems's most productive authors include Stephen Grossberg, Ennio Mingolla, Gail A. Carpenter, Michael A. Cohen, Frank H. Guenther, Daniel Bullock, Stephen Grossberg, John H. Reynolds, S. Grossberg and Eric L. Schwartz.

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.

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