Michael D. Howard

1.0k total citations
23 papers, 585 citations indexed

About

Michael D. Howard is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Artificial Intelligence. According to data from OpenAlex, Michael D. Howard has authored 23 papers receiving a total of 585 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Cognitive Neuroscience, 5 papers in Cellular and Molecular Neuroscience and 5 papers in Artificial Intelligence. Recurrent topics in Michael D. Howard's work include Neural dynamics and brain function (5 papers), Neuroscience and Neuropharmacology Research (5 papers) and Memory and Neural Mechanisms (5 papers). Michael D. Howard is often cited by papers focused on Neural dynamics and brain function (5 papers), Neuroscience and Neuropharmacology Research (5 papers) and Memory and Neural Mechanisms (5 papers). Michael D. Howard collaborates with scholars based in United States. Michael D. Howard's co-authors include David W. Payton, Mike Daily, Rajan Bhattacharyya, Craig Lee, Nicholas Ketz, Randall C. O’Reilly, R.S. Wallace, Praveen K. Pilly, J. Jerald and Craig A. Lee and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Cognitive Science and Frontiers in Neuroscience.

In The Last Decade

Michael D. Howard

21 papers receiving 550 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Michael D. Howard United States 9 195 186 178 125 82 23 585
Elio Tuci Belgium 17 333 1.7× 205 1.1× 397 2.2× 200 1.6× 343 4.2× 71 1.1k
Orazio Miglino Italy 16 67 0.3× 173 0.9× 213 1.2× 143 1.1× 511 6.2× 63 1.1k
Frank Pasemann Germany 16 117 0.6× 265 1.4× 82 0.5× 23 0.2× 212 2.6× 51 637
Katsunori Shimohara Japan 17 51 0.3× 212 1.1× 63 0.4× 91 0.7× 346 4.2× 194 951
Luc Berthouze United Kingdom 19 46 0.2× 433 2.3× 45 0.3× 74 0.6× 165 2.0× 80 956
Takashi Miyaki Japan 16 48 0.2× 406 2.2× 88 0.5× 287 2.3× 36 0.4× 55 881
Marinus Maris Netherlands 8 50 0.3× 45 0.2× 35 0.2× 80 0.6× 100 1.2× 21 643
Paolo Gaudiano United States 13 114 0.6× 206 1.1× 24 0.1× 150 1.2× 125 1.5× 38 541
Daniel Drew United Kingdom 19 67 0.3× 285 1.5× 80 0.4× 70 0.6× 43 0.5× 42 878
Pablo Lanillos Netherlands 14 75 0.4× 273 1.5× 31 0.2× 145 1.2× 137 1.7× 38 599

Countries citing papers authored by Michael D. Howard

Since Specialization
Citations

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

Fields of papers citing papers by Michael D. Howard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael D. Howard. 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 Michael D. Howard. The network helps show where Michael D. Howard may publish in the future.

Co-authorship network of co-authors of Michael D. Howard

This figure shows the co-authorship network connecting the top 25 collaborators of Michael D. Howard. A scholar is included among the top collaborators of Michael D. Howard 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 Michael D. Howard. Michael D. Howard is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Jones, Aaron P., Teagan S. Mullins, Michael Trumbo, et al.. (2023). Closed-Loop tACS Delivered during Slow-Wave Sleep Reduces Retroactive Interference on a Paired-Associates Learning Task. Brain Sciences. 13(3). 468–468. 5 indexed citations
2.
Howard, Michael D., et al.. (2022). A model of bi-directional interactions between complementary learning systems for memory consolidation of sequential experiences. Frontiers in Systems Neuroscience. 16. 972235–972235. 4 indexed citations
3.
Parker, Robert, et al.. (2022). Evaluating the Oregon Experiential Learning Model: Findings from Clients, Students, and Alumni. Journal of Planning Education and Research. 44(3). 1122–1133. 1 indexed citations
4.
Pilly, Praveen K., Ryan Hubbard, Nicholas Ketz, et al.. (2020). One-Shot Tagging During Wake and Cueing During Sleep With Spatiotemporal Patterns of Transcranial Electrical Stimulation Can Boost Long-Term Metamemory of Individual Episodes in Humans. Frontiers in Neuroscience. 13. 1416–1416. 6 indexed citations
5.
Jones, Aaron P., Jaehoon Choe, Nicholas Ketz, et al.. (2018). Dose-Dependent Effects of Closed-Loop tACS Delivered During Slow-Wave Oscillations on Memory Consolidation. Frontiers in Neuroscience. 12. 867–867. 28 indexed citations
6.
Howard, Michael D., et al.. (2018). Mental State Assessment and Validation Using Personalized Physiological Biometrics. Frontiers in Human Neuroscience. 12. 221–221. 14 indexed citations
7.
Pilly, Praveen K., Michael D. Howard, & Rajan Bhattacharyya. (2018). Modeling Contextual Modulation of Memory Associations in the Hippocampus. Frontiers in Human Neuroscience. 12. 442–442. 12 indexed citations
8.
Sapio, Vincent De, et al.. (2016). Demographic specific musculoskeletal models of factory worker performance, fatigue, and injury. 1–13. 1 indexed citations
9.
Howard, Michael D., et al.. (2015). The neural basis of decision-making during sensemaking: Implications for human-system interaction. 18. 1–16. 3 indexed citations
10.
Daily, Mike, et al.. (2013). Using a distracted driver's behavior to inform the timing of alerts in a semi-autonomous car. 199–202. 2 indexed citations
11.
Howard, Michael D., et al.. (2013). Using tactile displays to maintain situational awareness during driving. 228–237. 3 indexed citations
12.
Lester, Adam W., Michael D. Howard, Jean‐Marc Fellous, & Rajan Bhattacharyya. (2013). A computational model of perirhinal cortex: Gating and repair of input to the hippocampus. 145. 1–9.
13.
Howard, Michael D., et al.. (2013). Hippocampal Anatomy Supports the Use of Context in Object Recognition: A Computational Model. Computational Intelligence and Neuroscience. 2013. 1–19. 7 indexed citations
14.
O’Reilly, Randall C., Rajan Bhattacharyya, Michael D. Howard, & Nicholas Ketz. (2011). Complementary Learning Systems. Cognitive Science. 38(6). 1229–1248. 156 indexed citations
15.
Hoffmann, H., et al.. (2011). Fast pattern matching with time-delay neural networks. 2424–2429. 5 indexed citations
16.
Howard, Michael D., et al.. (2010). Further Explorations of a Minimal Polychronous Memory. International Conference on Artificial Intelligence. 17(4). 325–330. 2 indexed citations
17.
Howard, Michael D., et al.. (2003). Coalitions for distributed sensor fusion. 1. 636–642. 4 indexed citations
18.
Payton, David W., et al.. (2003). Compound behaviors in pheromone robotics. Robotics and Autonomous Systems. 44(3-4). 229–240. 52 indexed citations
19.
Daily, Mike, et al.. (2000). Distributed design review in virtual environments. 57–63. 40 indexed citations
20.
Wallace, R.S. & Michael D. Howard. (1989). HBA vision architecture: built and benchmarked. IEEE Transactions on Pattern Analysis and Machine Intelligence. 11(3). 227–232. 19 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.

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