Marja D. Sepers

1.8k total citations
24 papers, 1.2k citations indexed

About

Marja D. Sepers is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology and Pharmacology. According to data from OpenAlex, Marja D. Sepers has authored 24 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Cellular and Molecular Neuroscience, 12 papers in Molecular Biology and 7 papers in Pharmacology. Recurrent topics in Marja D. Sepers's work include Genetic Neurodegenerative Diseases (16 papers), Neuroscience and Neuropharmacology Research (15 papers) and Mitochondrial Function and Pathology (9 papers). Marja D. Sepers is often cited by papers focused on Genetic Neurodegenerative Diseases (16 papers), Neuroscience and Neuropharmacology Research (15 papers) and Mitochondrial Function and Pathology (9 papers). Marja D. Sepers collaborates with scholars based in Canada, United States and France. Marja D. Sepers's co-authors include Lynn A. Raymond, Olivier J. Manzoni, Amy Smith-Dijak, Clare M. Gladding, Olivier Lassalle, Austen J. Milnerwood, Daniela Neuhofer, István Katona, Christopher M. Henstridge and Ken Mackie and has published in prestigious journals such as Nature Communications, Journal of Neuroscience and Nature Neuroscience.

In The Last Decade

Marja D. Sepers

23 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Marja D. Sepers Canada 15 756 503 289 232 216 24 1.2k
Alberto Martire Italy 25 789 1.0× 562 1.1× 242 0.8× 160 0.7× 236 1.1× 47 1.6k
Walter J. Rushlow Canada 27 1.0k 1.4× 826 1.6× 684 2.4× 246 1.1× 94 0.4× 60 2.0k
Valérie Compan France 21 853 1.1× 539 1.1× 197 0.7× 210 0.9× 73 0.3× 39 1.4k
Giovanna Paolone Italy 20 783 1.0× 410 0.8× 107 0.4× 419 1.8× 125 0.6× 44 1.3k
Salvatore Lecca France 25 1.3k 1.7× 627 1.2× 383 1.3× 459 2.0× 125 0.6× 36 1.9k
Giuseppe Gangarossa France 20 719 1.0× 458 0.9× 80 0.3× 295 1.3× 147 0.7× 42 1.2k
Laura Caberlotto Italy 24 1.0k 1.4× 704 1.4× 123 0.4× 162 0.7× 40 0.2× 48 1.8k
Giuliano Grignaschi Italy 22 617 0.8× 425 0.8× 169 0.6× 67 0.3× 224 1.0× 32 1.2k
Yukio Takamatsu Japan 15 465 0.6× 365 0.7× 84 0.3× 207 0.9× 115 0.5× 32 1.1k
Emma Puighermanal France 16 850 1.1× 380 0.8× 750 2.6× 390 1.7× 60 0.3× 27 1.5k

Countries citing papers authored by Marja D. Sepers

Since Specialization
Citations

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

Fields of papers citing papers by Marja D. Sepers

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marja D. Sepers

This figure shows the co-authorship network connecting the top 25 collaborators of Marja D. Sepers. A scholar is included among the top collaborators of Marja D. Sepers 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 Marja D. Sepers. Marja D. Sepers 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
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Sepers, Marja D., et al.. (2024). Deep behavioural phenotyping of the Q175 Huntington disease mouse model: effects of age, sex, and weight. BMC Biology. 22(1). 121–121. 6 indexed citations
3.
Sepers, Marja D., et al.. (2023). Age- and region-dependent cortical excitability in the zQ175 Huntington disease mouse model. Human Molecular Genetics. 33(5). 387–399. 3 indexed citations
4.
Mackay, James P., et al.. (2023). Activin A targets extrasynaptic NMDA receptors to ameliorate neuronal and behavioral deficits in a mouse model of Huntington disease. Neurobiology of Disease. 189. 106360–106360. 4 indexed citations
5.
6.
Sepers, Marja D., James P. Mackay, Dongsheng Xiao, et al.. (2022). Altered cortical processing of sensory input in Huntington disease mouse models. Neurobiology of Disease. 169. 105740–105740. 9 indexed citations
7.
Sepers, Marja D., et al.. (2021). Regulation of hippocampal excitatory synapses by the Zdhhc5 palmitoyl acyltransferase. Journal of Cell Science. 134(9). 14 indexed citations
8.
Sepers, Marja D., et al.. (2021). Impaired Refinement of Kinematic Variability in Huntington Disease Mice on an Automated Home Cage Forelimb Motor Task. Journal of Neuroscience. 41(41). 8589–8602. 3 indexed citations
9.
Bilbao, Ainhoa, Daniela Neuhofer, Marja D. Sepers, et al.. (2020). Endocannabinoid LTD in Accumbal D1 Neurons Mediates Reward-Seeking Behavior. iScience. 23(3). 100951–100951. 26 indexed citations
10.
Sepers, Marja D., et al.. (2017). Endocannabinoid-Specific Impairment in Synaptic Plasticity in Striatum of Huntington's Disease Mouse Model. Journal of Neuroscience. 38(3). 544–554. 25 indexed citations
11.
Manduca, Antonia, Olivier Lassalle, Marja D. Sepers, et al.. (2016). Interacting Cannabinoid and Opioid Receptors in the Nucleus Accumbens Core Control Adolescent Social Play. Frontiers in Behavioral Neuroscience. 10. 211–211. 53 indexed citations
12.
Southwell, Amber L., Amy Smith-Dijak, Chris Kay, et al.. (2016). An enhanced Q175 knock-in mouse model of Huntington disease with higher mutant huntingtin levels and accelerated disease phenotypes. Human Molecular Genetics. 25(17). 3654–3675. 76 indexed citations
13.
Neuhofer, Daniela, Christopher M. Henstridge, Barna Dudok, et al.. (2015). Functional and structural deficits at accumbens synapses in a mouse model of Fragile X. Frontiers in Cellular Neuroscience. 9. 100–100. 35 indexed citations
14.
Sepers, Marja D. & Lynn A. Raymond. (2014). Mechanisms of synaptic dysfunction and excitotoxicity in Huntington's disease. Drug Discovery Today. 19(7). 990–996. 95 indexed citations
15.
Naydenov, Alipi V., et al.. (2014). Genetic rescue of CB1 receptors on medium spiny neurons prevents loss of excitatory striatal synapses but not motor impairment in HD mice. Neurobiology of Disease. 71. 140–150. 42 indexed citations
16.
Gladding, Clare M., et al.. (2013). Chronic blockade of extrasynaptic NMDA receptors ameliorates synaptic dysfunction and pro-death signaling in Huntington disease transgenic mice. Neurobiology of Disease. 62. 533–542. 67 indexed citations
17.
Jung, Kwang‐Mook, Marja D. Sepers, Christopher M. Henstridge, et al.. (2012). Uncoupling of the endocannabinoid signalling complex in a mouse model of fragile X syndrome. Nature Communications. 3(1). 1080–1080. 207 indexed citations
18.
Gladding, Clare M., Marja D. Sepers, Jian Xu, et al.. (2012). Calpain and STriatal-Enriched protein tyrosine Phosphatase (STEP) activation contribute to extrasynaptic NMDA receptor localization in a Huntington's disease mouse model. Human Molecular Genetics. 21(17). 3739–3752. 64 indexed citations
19.
Milnerwood, Austen J., Marja D. Sepers, Kevin She, et al.. (2012). Opposing Roles of Synaptic and Extrasynaptic NMDA Receptor Signaling in Cocultured Striatal and Cortical Neurons. Journal of Neuroscience. 32(12). 3992–4003. 108 indexed citations
20.
Milnerwood, Austen J., Marja D. Sepers, Clare M. Gladding, et al.. (2012). Mitigation of augmented extrasynaptic NMDAR signaling and apoptosis in cortico-striatal co-cultures from Huntington's disease mice. Neurobiology of Disease. 48(1). 40–51. 55 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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