Anna M. Monk

683 total citations
9 papers, 386 citations indexed

About

Anna M. Monk is a scholar working on Cognitive Neuroscience, Pharmacology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Anna M. Monk has authored 9 papers receiving a total of 386 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Cognitive Neuroscience, 2 papers in Pharmacology and 2 papers in Cellular and Molecular Neuroscience. Recurrent topics in Anna M. Monk's work include Memory and Neural Mechanisms (6 papers), Neural dynamics and brain function (3 papers) and Neuroscience and Neuropharmacology Research (2 papers). Anna M. Monk is often cited by papers focused on Memory and Neural Mechanisms (6 papers), Neural dynamics and brain function (3 papers) and Neuroscience and Neuropharmacology Research (2 papers). Anna M. Monk collaborates with scholars based in United Kingdom, Italy and Australia. Anna M. Monk's co-authors include Enrico Foglia, A. Carlo Altamura, Robin Murray, G. Camuri, Sagnik Bhattacharyya, Musa Sami, Tabea Schoeler, Ruth C. Brown, Ewa Klamerus and Eleanor A. Maguire and has published in prestigious journals such as NeuroImage, Clinical Psychology Review and Journal of Cognitive Neuroscience.

In The Last Decade

Anna M. Monk

8 papers receiving 382 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Anna M. Monk United Kingdom	6	179	141	111	60	57	9	386
Rosa Jurado‐Barba Spain	13	107 0.6×	81 0.6×	127 1.1×	118 2.0×	92 1.6×	50	482
M. Aurora Falcone United Kingdom	8	143 0.8×	227 1.6×	57 0.5×	68 1.1×	69 1.2×	12	355
Jenessa S. Price United States	10	286 1.6×	108 0.8×	120 1.1×	121 2.0×	51 0.9×	17	451
Killian A. Welch United Kingdom	9	77 0.4×	104 0.7×	99 0.9×	67 1.1×	41 0.7×	11	318
Karolina Kozak Canada	8	57 0.3×	95 0.7×	110 1.0×	74 1.2×	107 1.9×	14	374
Angelina Isabella Mellentin Denmark	11	63 0.4×	110 0.8×	83 0.7×	57 0.9×	113 2.0×	37	463
Siobhan Morse United States	9	58 0.3×	91 0.6×	57 0.5×	122 2.0×	45 0.8×	18	308
Jennifer L. Winward United States	6	202 1.1×	76 0.5×	121 1.1×	112 1.9×	73 1.3×	6	406
Mónica Jiménez Spain	8	58 0.3×	101 0.7×	108 1.0×	106 1.8×	94 1.6×	8	338
Kimberly R. Warren United States	7	69 0.4×	210 1.5×	47 0.4×	51 0.8×	54 0.9×	11	429

Countries citing papers authored by Anna M. Monk

Since Specialization

Citations

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

Fields of papers citing papers by Anna M. Monk

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Anna M. Monk. 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 Anna M. Monk. The network helps show where Anna M. Monk may publish in the future.

Co-authorship network of co-authors of Anna M. Monk

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

All Works

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9 of 9 papers shown

Monk, Anna M., Daniel N. Barry, Vladimir Litvak, Gareth R. Barnes, & Eleanor A. Maguire. (2021). Watching Movies Unfold, a Frame-by-Frame Analysis of the Associated Neural Dynamics. eNeuro. 8(4). ENEURO.0099–21.2021.

Clark, Ian A., Anna M. Monk, & Eleanor A. Maguire. (2020). Characterizing Strategy Use During the Performance of Hippocampal-Dependent Tasks. Frontiers in Psychology. 11. 2119–2119. 14 indexed citations

Clark, Ian A., et al.. (2020). Does hippocampal volume explain performance differences on hippocampal-dependant tasks?. NeuroImage. 221. 117211–117211. 32 indexed citations

Monk, Anna M., Marshall A. Dalton, Gareth R. Barnes, & Eleanor A. Maguire. (2020). The Role of Hippocampal–Ventromedial Prefrontal Cortex Neural Dynamics in Building Mental Representations. Journal of Cognitive Neuroscience. 33(1). 89–103. 25 indexed citations

Monk, Anna M., Gareth R. Barnes, & Eleanor A. Maguire. (2020). The Effect of Object Type on Building Scene Imagery—an MEG Study. Frontiers in Human Neuroscience. 14. 592175–592175. 3 indexed citations

Clark, Ian A., et al.. (2019). Identifying the cognitive processes underpinning hippocampal-dependent tasks.. Journal of Experimental Psychology General. 148(11). 1861–1881. 28 indexed citations

Schoeler, Tabea, Anna M. Monk, Musa Sami, et al.. (2016). Continued versus discontinued cannabis use in patients with psychosis: a systematic review and meta-analysis. The Lancet Psychiatry. 3(3). 215–225. 222 indexed citations

Barnard, Katharine, Pamela Dyson, Sue Cradock, et al.. (2015). A feasibility assessment of a web based cognitive behaviour therapy tool for treating depression in people with diabetes. Diabetic Medicine. 32. 184–184. 1 indexed citations

Matcham, Faith, Lauren Rayner, Jane Hutton, et al.. (2014). Self-help interventions for symptoms of depression, anxiety and psychological distress in patients with physical illnesses: A systematic review and meta-analysis. Clinical Psychology Review. 34(2). 141–157. 61 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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