Mark B. Moss

9.6k total citations · 1 hit paper
96 papers, 7.3k citations indexed

About

Mark B. Moss is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Psychiatry and Mental health. According to data from OpenAlex, Mark B. Moss has authored 96 papers receiving a total of 7.3k indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Cognitive Neuroscience, 23 papers in Cellular and Molecular Neuroscience and 21 papers in Psychiatry and Mental health. Recurrent topics in Mark B. Moss's work include Memory and Neural Mechanisms (31 papers), Neuroscience and Neuropharmacology Research (18 papers) and Dementia and Cognitive Impairment Research (16 papers). Mark B. Moss is often cited by papers focused on Memory and Neural Mechanisms (31 papers), Neuroscience and Neuropharmacology Research (18 papers) and Dementia and Cognitive Impairment Research (16 papers). Mark B. Moss collaborates with scholars based in United States, United Kingdom and Spain. Mark B. Moss's co-authors include Ronald Killiany, Douglas L. Rosene, Rudolph E. Tanzi, Marilyn Albert, Ferenc A. Jólesz, James G. Herndon, Helen Mahut, Marilyn S. Albert, Stuart Zola‐Morgan and Alan Peters and has published in prestigious journals such as Journal of Neuroscience, SHILAP Revista de lepidopterología and Neurology.

In The Last Decade

Mark B. Moss

94 papers receiving 7.1k citations

Hit Papers

Use of structural magnetic resonance imaging to predict w... 2000 2026 2008 2017 2000 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mark B. Moss United States 43 3.2k 2.1k 2.0k 1.7k 1.4k 96 7.3k
Mikko P. Laakso Finland 45 2.8k 0.9× 3.4k 1.6× 2.7k 1.4× 1.1k 0.6× 1.2k 0.8× 86 7.6k
Zhijun Zhang China 51 4.0k 1.3× 2.0k 0.9× 1.4k 0.7× 2.0k 1.1× 1.4k 1.0× 357 10.2k
Susan De Santi United States 49 2.7k 0.9× 4.3k 2.0× 4.3k 2.2× 976 0.6× 1.5k 1.0× 110 9.8k
Michael A. Yassa United States 42 5.4k 1.7× 1.5k 0.7× 1.3k 0.6× 2.5k 1.4× 750 0.5× 149 8.2k
Georg Winterer Germany 53 4.8k 1.5× 1.7k 0.8× 1.1k 0.5× 1.8k 1.1× 506 0.4× 203 8.9k
Christoph Höck Switzerland 48 1.6k 0.5× 1.0k 0.5× 3.1k 1.6× 1.5k 0.9× 1.2k 0.9× 144 7.9k
Kristen M. Kennedy United States 47 5.4k 1.7× 3.1k 1.5× 1.6k 0.8× 1.3k 0.8× 1.1k 0.8× 144 10.9k
Pantéleimon Giannakopoulos Switzerland 59 3.1k 1.0× 3.6k 1.7× 3.7k 1.9× 1.2k 0.7× 2.0k 1.4× 269 10.7k
Mark B. Schapiro United States 49 3.0k 0.9× 2.2k 1.0× 1.8k 0.9× 741 0.4× 615 0.4× 128 7.3k
Helmut Heinsen Germany 47 2.4k 0.8× 1.4k 0.7× 2.1k 1.1× 2.3k 1.3× 1.3k 0.9× 138 7.4k

Countries citing papers authored by Mark B. Moss

Since Specialization
Citations

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

Fields of papers citing papers by Mark B. Moss

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mark B. Moss. 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 Mark B. Moss. The network helps show where Mark B. Moss may publish in the future.

Co-authorship network of co-authors of Mark B. Moss

This figure shows the co-authorship network connecting the top 25 collaborators of Mark B. Moss. A scholar is included among the top collaborators of Mark B. Moss 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 Mark B. Moss. Mark B. Moss 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
2.
Moss, Mark B., et al.. (2021). Curcumin improves reversal learning in middle-aged rhesus monkeys.. Behavioral Neuroscience. 136(2). 126–138. 2 indexed citations
3.
Chang, Andrew, et al.. (2018). Quantification of discrete behavioral components of the MDS-UPDRS. Journal of Clinical Neuroscience. 61. 174–179. 5 indexed citations
4.
Moore, Tara L., Ronald Killiany, Monica A. Pessina, et al.. (2011). Recovery from ischemia in the middle-aged brain: a nonhuman primate model. Neurobiology of Aging. 33(3). 619.e9–619.e24. 25 indexed citations
5.
Wisco, Jonathan J., Ronald Killiany, Charles R.G. Guttmann, et al.. (2007). An MRI study of age-related white and gray matter volume changes in the rhesus monkey. Neurobiology of Aging. 29(10). 1563–1575. 64 indexed citations
6.
Moore, Tara L., Ronald Killiany, James G. Herndon, Douglas L. Rosene, & Mark B. Moss. (2005). Executive system dysfunction occurs as early as middle-age in the rhesus monkey. Neurobiology of Aging. 27(10). 1484–1493. 100 indexed citations
7.
Lacreuse, Agnès, Douglas L. Rosene, Ronald Killiany, et al.. (2005). Sex, Age, and Training Modulate Spatial Memory in the Rhesus Monkey (Macaca mulatta).. Behavioral Neuroscience. 119(1). 118–126. 58 indexed citations
8.
Moss, Mark B., et al.. (2004). Subtalar arthrodesis. Clinics in Podiatric Medicine and Surgery. 21(2). 179–201. 6 indexed citations
9.
Rehbein, Lucio & Mark B. Moss. (2002). Explorations of three modes of spatial cognition in the monkey. SHILAP Revista de lepidopterología. 3 indexed citations
10.
Albert, Marilyn S., Mark B. Moss, Rudolph E. Tanzi, & Kenneth W. Jones. (2001). Preclinical prediction of AD using neuropsychological tests. Journal of the International Neuropsychological Society. 7(5). 631–639. 431 indexed citations
11.
Herndon, James G., Ioannis Constantinidis, & Mark B. Moss. (1998). Age-related brain changes in rhesus monkeys. Neuroreport. 9(9). 2127–2130. 9 indexed citations
12.
Moss, Mark B., Ronald Killiany, Zona Lai, Douglas L. Rosene, & James G. Herndon. (1997). Recognition memory span in rhesus monkeys of advanced age. Neurobiology of Aging. 18(1). 13–19. 83 indexed citations
13.
Piccini, Paola, David J. Burn, N. Turjanski, et al.. (1995). DOPAMINERGIC FUNCTION IN RELATIVES OF PARKINSONS-DISEASE PATIENTS - A CLINICAL AND PET STUDY. UCL Discovery (University College London). 1 indexed citations
14.
Lai, Zona, Mark B. Moss, Ronald Killiany, Douglas L. Rosene, & James G. Herndon. (1995). Executive system dysfunction in the aged monkey: Spatial and object reversal learning. Neurobiology of Aging. 16(6). 947–954. 142 indexed citations
15.
Poduri, Annapurna, Lori L. Beason‐Held, Mark B. Moss, Douglas L. Rosene, & Bradley T. Hyman. (1995). CA3 neuronal degeneration follows chronic entorhinal cortex lesions. Neuroscience Letters. 197(1). 1–4. 23 indexed citations
16.
Hyman, Bradley T., et al.. (1994). Extracellular signal-regulated kinase (MAP kinase) immunoreactivity in the rhesus monkey brain. Neuroscience Letters. 166(1). 113–116. 11 indexed citations
17.
Moss, Mark B., et al.. (1994). The Effects of Aging on Area 46 of the Frontal Cortex of the Rhesus Monkey. Cerebral Cortex. 4(6). 621–635. 163 indexed citations
18.
Moss, Mark B.. (1993). The longitudinal assessment of recognition memory in aged rhesus monkeys. Neurobiology of Aging. 14(6). 635–636. 15 indexed citations
19.
White, Roberta F., Robert G. Feldman, Mark B. Moss, & Susan P. Proctor. (1993). Magnetic Resonance Imaging (MRI), Neurobehavioral Testing, and Toxic Encephalopathy: Two Cases. Environmental Research. 61(1). 117–123. 20 indexed citations
20.
Moss, Mark B., Douglas L. Rosene, & Alan Peters. (1988). Effects of aging on visual recognition memory in the rhesus monkey. Neurobiology of Aging. 9(5-6). 495–502. 143 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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