Alexa Tompary

1.7k total citations
21 papers, 762 citations indexed

About

Alexa Tompary is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Artificial Intelligence. According to data from OpenAlex, Alexa Tompary has authored 21 papers receiving a total of 762 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Cognitive Neuroscience, 7 papers in Cellular and Molecular Neuroscience and 4 papers in Artificial Intelligence. Recurrent topics in Alexa Tompary's work include Memory and Neural Mechanisms (19 papers), Memory Processes and Influences (12 papers) and Neuroscience and Neuropharmacology Research (7 papers). Alexa Tompary is often cited by papers focused on Memory and Neural Mechanisms (19 papers), Memory Processes and Influences (12 papers) and Neuroscience and Neuropharmacology Research (7 papers). Alexa Tompary collaborates with scholars based in United States and Canada. Alexa Tompary's co-authors include Lila Davachi, Katherine Duncan, Sharon L. Thompson‐Schill, Vishnu P. Murty, R. Alison Adcock, Elizabeth A. Phelps, Jared F. Danker, Nicholas B. Turk‐Browne, Oriel FeldmanHall and Lindsay E. Hunter and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Neuron and Journal of Neuroscience.

In The Last Decade

Alexa Tompary

21 papers receiving 749 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Alexa Tompary United States 14 687 188 99 86 66 21 762
Nicole M. Long United States 16 810 1.2× 155 0.8× 101 1.0× 81 0.9× 23 0.3× 27 913
Aaron M. Bornstein United States 14 661 1.0× 154 0.8× 131 1.3× 94 1.1× 21 0.3× 32 842
Reka Daniel United States 8 582 0.8× 73 0.4× 142 1.4× 80 0.9× 19 0.3× 9 757
Karen F. LaRocque United States 10 645 0.9× 154 0.8× 65 0.7× 61 0.7× 12 0.2× 13 693
Yael Shrager United States 10 788 1.1× 325 1.7× 56 0.6× 104 1.2× 32 0.5× 11 864
Jennifer J. Summerfield United Kingdom 6 767 1.1× 97 0.5× 140 1.4× 139 1.6× 22 0.3× 6 859
Anwar O. Núñez-Elizalde United States 8 487 0.7× 56 0.3× 214 2.2× 56 0.7× 120 1.8× 10 709
Marie St‐Laurent Canada 16 831 1.2× 194 1.0× 89 0.9× 208 2.4× 25 0.4× 21 925
Serra E. Favila United States 8 540 0.8× 165 0.9× 34 0.3× 59 0.7× 23 0.3× 9 586
Francesco Mannella Italy 14 312 0.5× 135 0.7× 52 0.5× 37 0.4× 23 0.3× 29 507

Countries citing papers authored by Alexa Tompary

Since Specialization
Citations

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

Fields of papers citing papers by Alexa Tompary

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alexa Tompary

This figure shows the co-authorship network connecting the top 25 collaborators of Alexa Tompary. A scholar is included among the top collaborators of Alexa Tompary 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 Alexa Tompary. Alexa Tompary 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.
Tompary, Alexa, et al.. (2023). Disruption of Anterior Temporal Lobe Reduces Distortions in Memory From Category Knowledge. Journal of Cognitive Neuroscience. 35(12). 1899–1918. 2 indexed citations
3.
Tompary, Alexa, et al.. (2022). Agency enhances temporal order memory in an interactive exploration game. Psychonomic Bulletin & Review. 29(6). 2219–2228. 2 indexed citations
4.
5.
Tompary, Alexa & Sharon L. Thompson‐Schill. (2021). Semantic influences on episodic memory distortions.. Journal of Experimental Psychology General. 150(9). 1800–1824. 33 indexed citations
6.
Callaghan, Bridget, Jennifer A. Silvers, Michelle VanTieghem, et al.. (2020). Age-Related Increases in Posterior Hippocampal Granularity Are Associated with Remote Detailed Episodic Memory in Development. Journal of Neuroscience. 41(8). 1738–1754. 17 indexed citations
7.
Tompary, Alexa, Wenxi Zhou, & Lila Davachi. (2020). Schematic memories develop quickly, but are not expressed unless necessary. Scientific Reports. 10(1). 16968–16968. 24 indexed citations
8.
Tompary, Alexa & Sharon L. Thompson‐Schill. (2020). Semantic influences on episodic memory distortions. PsyArXiv (OSF Preprints). 5 indexed citations
9.
Kenett, Yoed N., Alexa Tompary, & Sharon L. Thompson‐Schill. (2019). How the Organization of Autobiographical Memories Changes Over Time.. Cognitive Science. 3294. 1 indexed citations
10.
Tompary, Alexa, Naseem Al-Aidroos, & Nicholas B. Turk‐Browne. (2018). Attending to What and Where: Background Connectivity Integrates Categorical and Spatial Attention. Journal of Cognitive Neuroscience. 30(9). 1281–1297. 20 indexed citations
11.
Goldfarb, Elizabeth V., Alexa Tompary, Lila Davachi, & Elizabeth A. Phelps. (2018). Acute stress throughout the memory cycle: Diverging effects on associative and item memory.. Journal of Experimental Psychology General. 148(1). 13–29. 40 indexed citations
12.
Bein, Oded, Niv Reggev, & Alexa Tompary. (2018). Working with Schemas, Predicting with Schemas. Journal of Neuroscience. 38(7). 1608–1610. 2 indexed citations
13.
FeldmanHall, Oriel, Joseph E. Dunsmoor, Alexa Tompary, et al.. (2018). Stimulus generalization as a mechanism for learning to trust. Proceedings of the National Academy of Sciences. 115(7). E1690–E1697. 68 indexed citations
14.
Tompary, Alexa & Lila Davachi. (2017). Consolidation Promotes the Emergence of Representational Overlap in the Hippocampus and Medial Prefrontal Cortex. Neuron. 96(1). 228–241.e5. 135 indexed citations
15.
Murty, Vishnu P., Alexa Tompary, R. Alison Adcock, & Lila Davachi. (2017). Selectivity in Postencoding Connectivity with High-Level Visual Cortex Is Associated with Reward-Motivated Memory. Journal of Neuroscience. 37(3). 537–545. 6 indexed citations
16.
Danker, Jared F., Alexa Tompary, & Lila Davachi. (2016). Trial-by-Trial Hippocampal Encoding Activation Predicts the Fidelity of Cortical Reinstatement During Subsequent Retrieval. Cerebral Cortex. 27(7). bhw146–bhw146. 46 indexed citations
17.
Córdova, Natalia I., Alexa Tompary, & Nicholas B. Turk‐Browne. (2016). Attentional modulation of background connectivity between ventral visual cortex and the medial temporal lobe. Neurobiology of Learning and Memory. 134. 115–122. 20 indexed citations
18.
Tompary, Alexa, Katherine Duncan, & Lila Davachi. (2016). High‐resolution investigation of memory‐specific reinstatement in the hippocampus and perirhinal cortex. Hippocampus. 26(8). 995–1007. 59 indexed citations
19.
Murty, Vishnu P., Alexa Tompary, R. Alison Adcock, & Lila Davachi. (2016). Selectivity in Postencoding Connectivity with High-Level Visual Cortex Is Associated with Reward-Motivated Memory. Journal of Neuroscience. 37(3). 537–545. 99 indexed citations
20.
Duncan, Katherine, Alexa Tompary, & Lila Davachi. (2014). Associative Encoding and Retrieval Are Predicted by Functional Connectivity in Distinct Hippocampal Area CA1 Pathways. Journal of Neuroscience. 34(34). 11188–11198. 82 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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