Michelle M. McCarthy

1.6k total citations
23 papers, 893 citations indexed

About

Michelle M. McCarthy is a scholar working on Cellular and Molecular Neuroscience, Cognitive Neuroscience and Neurology. According to data from OpenAlex, Michelle M. McCarthy has authored 23 papers receiving a total of 893 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Cellular and Molecular Neuroscience, 16 papers in Cognitive Neuroscience and 5 papers in Neurology. Recurrent topics in Michelle M. McCarthy's work include Neural dynamics and brain function (15 papers), Neuroscience and Neuropharmacology Research (14 papers) and Neuroscience and Neural Engineering (6 papers). Michelle M. McCarthy is often cited by papers focused on Neural dynamics and brain function (15 papers), Neuroscience and Neuropharmacology Research (14 papers) and Neuroscience and Neural Engineering (6 papers). Michelle M. McCarthy collaborates with scholars based in United States, United Kingdom and Australia. Michelle M. McCarthy's co-authors include Nancy Kopell, Emery N. Brown, Xue Han, Xiaosi Gu, Ed Boyden, Caroline Moore-Kochlacs, Miles A. Whittington, Shane Lee, Christoph Börgers and Jung H. Lee and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Neuroscience and SHILAP Revista de lepidopterología.

In The Last Decade

Michelle M. McCarthy

23 papers receiving 875 citations

Peers

Michelle M. McCarthy
Howard J. Faulkner United Kingdom
S. Matt Stead United States
Lynn Uhrig France
Richard J. Staba United States
W. Bryan Wilent United States
Andrew E. Hudson United States
Diany Paola Calderon United States
R. Llinás United States
Howard J. Faulkner United Kingdom
Michelle M. McCarthy
Citations per year, relative to Michelle M. McCarthy Michelle M. McCarthy (= 1×) peers Howard J. Faulkner

Countries citing papers authored by Michelle M. McCarthy

Since Specialization
Citations

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

Fields of papers citing papers by Michelle M. McCarthy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michelle M. McCarthy

This figure shows the co-authorship network connecting the top 25 collaborators of Michelle M. McCarthy. A scholar is included among the top collaborators of Michelle M. McCarthy 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 Michelle M. McCarthy. Michelle M. McCarthy 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.
Kowalski, M., Oluwaseun Akeju, Earl K. Miller, et al.. (2024). Ketamine can produce oscillatory dynamics by engaging mechanisms dependent on the kinetics of NMDA receptors. Proceedings of the National Academy of Sciences. 121(22). e2402732121–e2402732121. 8 indexed citations
2.
Cattani, Anna, Don B. Arnold, Michelle M. McCarthy, & Nancy Kopell. (2024). Basolateral amygdala oscillations enable fear learning in a biophysical model. eLife. 12. 3 indexed citations
3.
Brown, Emery N., et al.. (2023). Rapid thalamocortical network switching mediated by cortical synchronization underlies propofol-induced EEG signatures: a biophysical model. Journal of Neurophysiology. 130(1). 86–103. 7 indexed citations
4.
Cattani, Anna, Don B. Arnold, Michelle M. McCarthy, & Nancy Kopell. (2023). Basolateral amygdala oscillations enable fear learning in a biophysical model. eLife. 12. 3 indexed citations
5.
Quast, Kathleen B., et al.. (2023). Rapid synaptic and gamma rhythm signature of mouse critical period plasticity. Proceedings of the National Academy of Sciences. 120(2). e2123182120–e2123182120. 8 indexed citations
6.
Brown, Emery N., et al.. (2022). Deep brain stimulation in the subthalamic nucleus for Parkinson’s disease can restore dynamics of striatal networks. Proceedings of the National Academy of Sciences. 119(19). e2120808119–e2120808119. 28 indexed citations
7.
McCarthy, Michelle M., et al.. (2020). A biophysical model of striatal microcircuits suggests gamma and beta oscillations interleaved at delta/theta frequencies mediate periodicity in motor control. PLoS Computational Biology. 16(2). e1007300–e1007300. 19 indexed citations
8.
Ardid, Salva, Jason Sherfey, Michelle M. McCarthy, et al.. (2019). Biased competition in the absence of input bias revealed through corticostriatal computation. Proceedings of the National Academy of Sciences. 116(17). 8564–8569. 10 indexed citations
9.
Pittman-Polletta, Benjamin, Ali Mohammed, Michael F. Romano, et al.. (2018). Striatal cholinergic receptor activation causes a rapid, selective and state‐dependent rise in cortico‐striatal β activity. European Journal of Neuroscience. 48(8). 2857–2868. 7 indexed citations
10.
Vo, Theodore, et al.. (2018). M-Current Expands the Range of Gamma Frequency Inputs to Which a Neuronal Target Entrains. SHILAP Revista de lepidopterología. 8(1). 13–13. 9 indexed citations
11.
McCarthy, Michelle M., Jason Sherfey, Shane Lee, et al.. (2017). Thalamocortical control of propofol phase-amplitude coupling. PLoS Computational Biology. 13(12). e1005879–e1005879. 39 indexed citations
12.
Kondabolu, Krishnakanth, et al.. (2016). Striatal cholinergic interneurons generate beta and gamma oscillations in the corticostriatal circuit and produce motor deficits. Proceedings of the National Academy of Sciences. 113(22). E3159–68. 74 indexed citations
13.
McCarthy, Michelle M., et al.. (2013). Excitable Neurons, Firing Threshold Manifolds and Canards. PubMed. 3(1). 12–12. 41 indexed citations
14.
McCarthy, Michelle M., ShiNung Ching, Miles A. Whittington, & Nancy Kopell. (2012). Dynamical changes in neurological diseases and anesthesia. Current Opinion in Neurobiology. 22(4). 693–703. 22 indexed citations
15.
McCarthy, Michelle M. & Nancy Kopell. (2012). The Effect of Propofol Anesthesia on Rebound Spiking. SIAM Journal on Applied Dynamical Systems. 11(4). 1674–1697. 8 indexed citations
16.
McCarthy, Michelle M., Caroline Moore-Kochlacs, Xiaosi Gu, et al.. (2011). Striatal origin of the pathologic beta oscillations in Parkinson's disease. Proceedings of the National Academy of Sciences. 108(28). 11620–11625. 224 indexed citations
17.
McCarthy, Michelle M., Emery N. Brown, & Nancy Kopell. (2008). Potential Network Mechanisms Mediating Electroencephalographic Beta Rhythm Changes during Propofol-Induced Paradoxical Excitation. Journal of Neuroscience. 28(50). 13488–13504. 122 indexed citations
18.
Rumsey, William L., David Aharony, Russell Bialecki, et al.. (2001). Pharmacological Characterization of ZD6021: A Novel, Orally Active Antagonist of the Tachykinin Receptors. Journal of Pharmacology and Experimental Therapeutics. 298(1). 307–315. 25 indexed citations
19.
Krell, Robert D. & Michelle M. McCarthy. (1991). Pharmacologic Analysis of Platelet Activating Factor16‐ and 18‐Induced Bronchoconstriction in the Guinea Pig. Annals of the New York Academy of Sciences. 629(1). 176–192. 1 indexed citations
20.
Snyder, David W., et al.. (1988). Conscious guinea-pig aerosol model for evaluation of peptide leukotriene antagonists. Journal of Pharmacological Methods. 19(3). 219–231. 6 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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