Ada Aka

613 citations
12 papers · 313 · h-index 6

Impact in

    • EEG and Brain-Computer Interfaces
    • Neural dynamics and brain function
    • Functional Brain Connectivity Studies
    • Memory and Neural Mechanisms
    • Memory Processes and Influences
    • Neural and Behavioral Psychology Studies
    • Neuroscience and Neural Engineering

Papers in

Ada Aka

12 papers receiving 307 citations

Peers

Ada Aka
Comparison fields: 5 of 63
  • Cognitive Neuroscience 201
  • Cellular and Molecular Neuroscience 82
  • Neurology 50
  • Neurology 25
  • General Decision Sciences 5
Replace Pierre Baraduc with:
Pierre Baraduc France
Anthony I. Jang United States
Jonathan Strunk United States
Kyle Dunovan United States
Andrew Clouter United Kingdom
Romain Brasselet France
Kamin Kim United States
Uros Topalovic United States
Damien Benis Switzerland
Pierre Petitet United Kingdom
Ada Aka relative to Pierre Baraduc France Pierre Baraduc's profile →
Citations per field
00.5×2×4×6×8×9.3×
Pierre Baraduc · 1×
Citations per year

Countries citing papers authored by Ada Aka

Since Specialization
Citations

This map shows the geographic impact of Ada Aka'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 Ada Aka with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ada Aka more than expected).

Fields of papers citing papers by Ada Aka

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ada Aka. 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 Ada Aka. The network helps show where Ada Aka may publish in the future.

Co-authors

The 25 scholars most cited alongside Ada Aka, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ada Aka Line = papers co-authored together Ada Aka links everyone, so they are left out of the graph.

All Works

12 of 12 papers shown
#Work
1 2018223
2 202035
3 202217
4 202313
5 20217
6 20256
7 20213
8 20243
9 20223
10
What I Like Is What I Remember: Memory Modulation in Preferential Choice
20201
11 20241
12 20241

About Ada Aka

Ada Aka is a scholar working on Cognitive Neuroscience, General Decision Sciences, Artificial Intelligence, Social Psychology and Information Systems and Management, having authored 12 papers that have together received 313 indexed citations. Recurring topics across this work include Memory Processes and Influences (5 papers), Topic Modeling (3 papers), Neural and Behavioral Psychology Studies (2 papers), Cognitive Science and Mapping (2 papers), Decision-Making and Behavioral Economics (2 papers), Mental Health via Writing (1 paper), Deception detection and forensic psychology (1 paper) and Information Retrieval and Search Behavior (1 paper). The work is most often cited by research in Cognitive Neuroscience (201 citations), Cellular and Molecular Neuroscience (82 citations), Neurology (50 citations), Neurology (25 citations) and General Decision Sciences (5 citations). Ada Aka has collaborated with scholars based in United States, Australia and Germany. Frequent co-authors include Sudeep Bhatia, Michael J. Kahana, John Philip McCoy, Russell Richie, Nicole M. Long, Lynn J. Lohnas, Nicole E. Miller‐Struttmann, Christoph T. Weidemann, Gerald Häubl and Ben Rhodri Newell. Their work appears in journals such as Journal of Experimental Psychology Learning Memory and Cognition, Cognition, Journal of the Association for Consumer Research, Nature Communications and Current Directions in Psychological Science.

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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