Fulva Shah

971 total citations
11 papers, 742 citations indexed

About

Fulva Shah is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology and Cognitive Neuroscience. According to data from OpenAlex, Fulva Shah has authored 11 papers receiving a total of 742 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Cellular and Molecular Neuroscience, 7 papers in Molecular Biology and 6 papers in Cognitive Neuroscience. Recurrent topics in Fulva Shah's work include Neuroscience and Neuropharmacology Research (10 papers), Receptor Mechanisms and Signaling (7 papers) and Neural dynamics and brain function (5 papers). Fulva Shah is often cited by papers focused on Neuroscience and Neuropharmacology Research (10 papers), Receptor Mechanisms and Signaling (7 papers) and Neural dynamics and brain function (5 papers). Fulva Shah collaborates with scholars based in United States, Russia and Netherlands. Fulva Shah's co-authors include James M. Tepper, Tibor Koós, Fatuel Tecuapetla, Osvaldo Ibáñez-Sandoval, Maxime Assous, Margaret E. Rice, Jyoti C. Patel, Daniel F. English, Harry S. Xenias and Joshua R. Berlin and has published in prestigious journals such as Nature Communications, Journal of Neuroscience and Cell Reports.

In The Last Decade

Fulva Shah

11 papers receiving 735 citations

Peers

Fulva Shah

CMN

CN

MB

NEURO

SP

Muhammad O. Chohan United States

Maxime Assous United States

Xiusong Wang China

Sylvie Pérez France

Vivien Zell United States

Matthieu Maroteaux United States

Qiaoling Cui United States

Katharine L. Altemus United States

Marie Vandecasteele France

Margriet J. Dolleman-Van der Weel Netherlands

Muhammad O. Chohan United States

Fulva Shah

450 ×0.7

CMN

211 ×0.7

CN

223 ×0.7

MB

110 ×0.8

NEURO

52 ×1.3

SP

Citations per year, relative to Fulva Shah Fulva Shah (= 1×) peers Muhammad O. Chohan

Countries citing papers authored by Fulva Shah

Since Specialization

Citations

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

Fields of papers citing papers by Fulva Shah

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fulva Shah

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

All Works

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11 of 11 papers shown

1.

Shah, Fulva, et al.. (2022). Cholinergic control of striatal GABAergic microcircuits. Cell Reports. 41(4). 111531–111531. 17 indexed citations

2.

Assous, Maxime, Edward Martinez, Fulva Shah, et al.. (2019). Neuropilin 2 Signaling Mediates Corticostriatal Transmission, Spine Maintenance, and Goal-Directed Learning in Mice. Journal of Neuroscience. 39(45). 8845–8859. 20 indexed citations

3.

Assous, Maxime, et al.. (2018). Identification and Characterization of a Novel Spontaneously Active Bursty GABAergic Interneuron in the Mouse Striatum. Journal of Neuroscience. 38(25). 5688–5699. 24 indexed citations

4.

Assous, Maxime, et al.. (2017). Differential processing of thalamic information via distinct striatal interneuron circuits. Nature Communications. 8(1). 15860–15860. 64 indexed citations

5.

Faust, Thomas W., Maxime Assous, Fulva Shah, James M. Tepper, & Tibor Koós. (2015). Novel fast adapting interneurons mediate cholinergic‐induced fast GABA_A inhibitory postsynaptic currents in striatal spiny neurons. European Journal of Neuroscience. 42(2). 1764–1774. 47 indexed citations

6.

Shah, Fulva, et al.. (2013). Anatomical and electrophysiological changes in striatal TH interneurons after loss of the nigrostriatal dopaminergic pathway. Brain Structure and Function. 220(1). 331–349. 27 indexed citations

7.

Ibáñez-Sandoval, Osvaldo, et al.. (2011). A Novel Functionally Distinct Subtype of Striatal Neuropeptide Y Interneuron. Journal of Neuroscience. 31(46). 16757–16769. 111 indexed citations

8.

Ibáñez-Sandoval, Osvaldo, et al.. (2011). Distribution of Tyrosine Hydroxylase-Expressing Interneurons with Respect to Anatomical Organization of the Neostriatum. Frontiers in Systems Neuroscience. 5. 41–41. 22 indexed citations

9.

Tecuapetla, Fatuel, Jyoti C. Patel, Harry S. Xenias, et al.. (2010). Glutamatergic Signaling by Mesolimbic Dopamine Neurons in the Nucleus Accumbens. Journal of Neuroscience. 30(20). 7105–7110. 248 indexed citations

10.

Ibáñez-Sandoval, Osvaldo, et al.. (2010). Electrophysiological and Morphological Characteristics and Synaptic Connectivity of Tyrosine Hydroxylase-Expressing Neurons in Adult Mouse Striatum. Journal of Neuroscience. 30(20). 6999–7016. 109 indexed citations

11.

Brazhnik, E. S., Fulva Shah, & James M. Tepper. (2008). GABAergic Afferents Activate Both GABA_Aand GABA_BReceptors in Mouse Substantia Nigra Dopaminergic NeuronsIn Vivo. Journal of Neuroscience. 28(41). 10386–10398. 53 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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