Deborah E. Hannula

3.0k total citations
35 papers, 2.1k citations indexed

About

Deborah E. Hannula is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Computer Vision and Pattern Recognition. According to data from OpenAlex, Deborah E. Hannula has authored 35 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Cognitive Neuroscience, 9 papers in Cellular and Molecular Neuroscience and 4 papers in Computer Vision and Pattern Recognition. Recurrent topics in Deborah E. Hannula's work include Memory and Neural Mechanisms (20 papers), Memory Processes and Influences (16 papers) and Face Recognition and Perception (9 papers). Deborah E. Hannula is often cited by papers focused on Memory and Neural Mechanisms (20 papers), Memory Processes and Influences (16 papers) and Face Recognition and Perception (9 papers). Deborah E. Hannula collaborates with scholars based in United States, United Kingdom and Switzerland. Deborah E. Hannula's co-authors include Charan Ranganath, Neal J. Cohen, Daniel Tranel, Jennifer D. Ryan, Anthony J. Greene, Laura A. Libby, Daniel J. Simons, Melissa C. Duff, David E. Warren and Carol L. Baym and has published in prestigious journals such as Neuron, Journal of Neuroscience and Nature reviews. Neuroscience.

In The Last Decade

Deborah E. Hannula

34 papers receiving 2.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Deborah E. Hannula United States 20 1.8k 502 244 214 212 35 2.1k
Timothy L. Hodgson United Kingdom 27 1.6k 0.9× 199 0.4× 219 0.9× 219 1.0× 225 1.1× 91 2.4k
Elisha P. Merriam United States 19 2.0k 1.1× 173 0.3× 99 0.4× 219 1.0× 164 0.8× 47 2.4k
Christine N. Smith United States 20 1.4k 0.8× 519 1.0× 148 0.6× 116 0.5× 195 0.9× 39 1.7k
Jeff P. Hamm New Zealand 26 1.7k 0.9× 312 0.6× 379 1.6× 95 0.4× 243 1.1× 78 2.1k
Caroline E. Robertson United States 15 1.4k 0.8× 239 0.5× 196 0.8× 250 1.2× 118 0.6× 31 1.6k
Veit Stuphorn United States 27 2.9k 1.6× 429 0.9× 110 0.5× 238 1.1× 230 1.1× 45 3.3k
Jesse Rissman United States 28 3.9k 2.2× 421 0.8× 421 1.7× 279 1.3× 336 1.6× 46 4.4k
Freek van Ede United Kingdom 31 3.0k 1.7× 351 0.7× 133 0.5× 77 0.4× 281 1.3× 91 3.3k
Rebecca Lawson United Kingdom 24 2.0k 1.1× 218 0.4× 455 1.9× 268 1.3× 267 1.3× 64 2.5k
Stephan A. Brandt Germany 22 2.7k 1.5× 246 0.5× 109 0.4× 114 0.5× 247 1.2× 56 3.2k

Countries citing papers authored by Deborah E. Hannula

Since Specialization
Citations

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

Fields of papers citing papers by Deborah E. Hannula

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Deborah E. Hannula. 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 Deborah E. Hannula. The network helps show where Deborah E. Hannula may publish in the future.

Co-authorship network of co-authors of Deborah E. Hannula

This figure shows the co-authorship network connecting the top 25 collaborators of Deborah E. Hannula. A scholar is included among the top collaborators of Deborah E. Hannula 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 Deborah E. Hannula. Deborah E. Hannula 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.
2.
Hannula, Deborah E., et al.. (2023). Control of memory retrieval alters memory-based eye movements.. Journal of Experimental Psychology Learning Memory and Cognition. 50(8). 1199–1219. 1 indexed citations
3.
Hannula, Deborah E., et al.. (2023). Relational memory weakness in autism despite the use of a controlled encoding task. Frontiers in Psychology. 14. 1210259–1210259.
4.
Hannula, Deborah E., et al.. (2021). Temporal Regularity May Not Improve Memory for Item-Specific Detail. Frontiers in Psychology. 12. 623402–623402. 3 indexed citations
5.
Hannula, Deborah E., et al.. (2020). Attention capture by episodic long-term memory. Cognition. 201. 104312–104312. 12 indexed citations
6.
Hannula, Deborah E., et al.. (2018). Subliminal encoding and flexible retrieval of objects in scenes. Hippocampus. 28(9). 633–643. 17 indexed citations
7.
Helmstetter, Fred J., et al.. (2016). Eye movements are captured by a perceptually simple conditioned stimulus in the absence of explicit contingency knowledge.. Emotion. 16(8). 1157–1171. 14 indexed citations
8.
Henke, Katharina, et al.. (2015). Relational Memory Is Evident in Eye Movement Behavior despite the Use of Subliminal Testing Methods. PLoS ONE. 10(10). e0141677–e0141677. 11 indexed citations
9.
Cooper, Rose A., Kate Plaisted-Grant, Deborah E. Hannula, et al.. (2015). Impaired recollection of visual scene details in adults with autism spectrum conditions.. Journal of Abnormal Psychology. 124(3). 565–575. 22 indexed citations
10.
Hannula, Deborah E., et al.. (2014). Memory for items and relationships among items embedded in realistic scenes: Disproportionate relational memory impairments in amnesia.. Neuropsychology. 29(1). 126–138. 23 indexed citations
11.
Libby, Laura A., Deborah E. Hannula, & Charan Ranganath. (2014). Medial Temporal Lobe Coding of Item and Spatial Information during Relational Binding in Working Memory. Journal of Neuroscience. 34(43). 14233–14242. 85 indexed citations
12.
Hannula, Deborah E. & Anthony J. Greene. (2012). The hippocampus reevaluated in unconscious learning and memory: at a tipping point?. Frontiers in Human Neuroscience. 6. 80–80. 98 indexed citations
13.
Ragland, J. Daniel, et al.. (2011). CNTRICS Imaging Biomarkers Final Task Selection: Long-Term Memory and Reinforcement Learning. Schizophrenia Bulletin. 38(1). 62–72. 19 indexed citations
14.
Chua, Elizabeth F., Deborah E. Hannula, & Charan Ranganath. (2011). Distinguishing highly confident accurate and inaccurate memory: Insights about relevant and irrelevant influences on memory confidence. Memory. 20(1). 48–62. 35 indexed citations
15.
Hannula, Deborah E., Charan Ranganath, Ian S. Ramsay, et al.. (2010). Use of Eye Movement Monitoring to Examine Item and Relational Memory in Schizophrenia. Biological Psychiatry. 68(7). 610–616. 31 indexed citations
16.
Hannula, Deborah E. & Charan Ranganath. (2009). The Eyes Have It: Hippocampal Activity Predicts Expression of Memory in Eye Movements. Neuron. 63(5). 592–599. 233 indexed citations
17.
Hannula, Deborah E. & Charan Ranganath. (2008). Medial Temporal Lobe Activity Predicts Successful Relational Memory Binding. Journal of Neuroscience. 28(1). 116–124. 208 indexed citations
18.
Thomas, Ayanna K., Deborah E. Hannula, & Elizabeth F. Loftus. (2006). How self‐relevant imagination affects memory for behaviour. Applied Cognitive Psychology. 21(1). 69–86. 14 indexed citations
19.
Hannula, Deborah E., Daniel J. Simons, & Neal J. Cohen. (2005). Imaging implicit perception: promise and pitfalls. Nature reviews. Neuroscience. 6(3). 247–255. 115 indexed citations
20.
Hannula, Deborah E., Daniel J. Simons, & Neal J. Cohen. (2005). Objective measures of awareness: why not aim higher?. Nature reviews. Neuroscience. 6(3). 258–258. 1 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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