Michael C. Quirk

5.2k total citations · 1 hit paper
37 papers, 3.7k citations indexed

About

Michael C. Quirk is a scholar working on Cellular and Molecular Neuroscience, Cognitive Neuroscience and Molecular Biology. According to data from OpenAlex, Michael C. Quirk has authored 37 papers receiving a total of 3.7k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Cellular and Molecular Neuroscience, 19 papers in Cognitive Neuroscience and 13 papers in Molecular Biology. Recurrent topics in Michael C. Quirk's work include Neuroscience and Neuropharmacology Research (28 papers), Memory and Neural Mechanisms (16 papers) and Neural dynamics and brain function (11 papers). Michael C. Quirk is often cited by papers focused on Neuroscience and Neuropharmacology Research (28 papers), Memory and Neural Mechanisms (16 papers) and Neural dynamics and brain function (11 papers). Michael C. Quirk collaborates with scholars based in United States, Australia and Japan. Michael C. Quirk's co-authors include Matthew A. Wilson, Matthew Wilson, Susumu Tonegawa, Kazu Nakazawa, Linus D. Sun, Loren M. Frank, Emery N. Brown, Mayank Mehta, Masahiko Watanabe and Daniel Johnston and has published in prestigious journals such as Science, Neuron and Journal of Neuroscience.

In The Last Decade

Michael C. Quirk

37 papers receiving 3.6k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Requirement for Hippocampal CA3 NMDA Receptors in Associative Memory Recall

2002 802 citations Kazu Nakazawa, Michael C. Quirk et al. Science profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Michael C. Quirk United States	22	2.4k	2.4k	708	377	320	37	3.7k
Michael J. Higley United States	30	2.8k 1.2×	2.0k 0.8×	1.4k 2.0×	282 0.7×	268 0.8×	53	4.3k
Melissa R. Warden United States	19	2.4k 1.0×	3.0k 1.2×	644 0.9×	216 0.6×	201 0.6×	30	4.9k
Graham V. Williams United States	25	2.8k 1.2×	2.8k 1.2×	1.3k 1.8×	328 0.9×	202 0.6×	41	5.2k
Joseph O’Neill United States	46	2.8k 1.2×	4.1k 1.7×	652 0.9×	245 0.6×	568 1.8×	131	6.6k
Christophe D. Proulx Canada	16	1.7k 0.7×	1.0k 0.4×	707 1.0×	240 0.6×	172 0.5×	24	2.7k
Charles R. Yang United States	28	3.4k 1.4×	2.4k 1.0×	1.6k 2.2×	284 0.8×	219 0.7×	52	5.0k
Alex C. Kwan United States	24	1.9k 0.8×	1.3k 0.6×	515 0.7×	209 0.6×	138 0.4×	62	3.1k
Adam G. Carter United States	29	2.6k 1.1×	1.8k 0.7×	1.1k 1.6×	195 0.5×	258 0.8×	35	3.4k
Paul J. Fitzgerald United States	31	1.3k 0.5×	1.9k 0.8×	575 0.8×	279 0.7×	225 0.7×	90	3.5k

Countries citing papers authored by Michael C. Quirk

Since Specialization

Citations

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

Fields of papers citing papers by Michael C. Quirk

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael C. Quirk. 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 Michael C. Quirk. The network helps show where Michael C. Quirk may publish in the future.

Co-authorship network of co-authors of Michael C. Quirk

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

All Works

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20 of 20 papers shown

Gray, Sarah M., Jing Dai, Anne C. Smith, et al.. (2024). Changes in 24(S)-Hydroxycholesterol Are Associated with Cognitive Performance in Early Huntington’s Disease: Data from the TRACK and ENROLL HD Cohorts. Journal of Huntington s Disease. 13(4). 449–465. 5 indexed citations

Tang, Weiting, Jacob T. Beckley, Jin Zhang, et al.. (2023). Novel neuroactive steroids as positive allosteric modulators of NMDA receptors: mechanism, site of action, and rescue pharmacology on GRIN variants associated with neurological conditions. Cellular and Molecular Life Sciences. 80(2). 42–42. 11 indexed citations

Hill, Matthew D., María‐Jesús Blanco, Francesco G. Salituro, et al.. (2022). SAGE-718: A First-in-ClassN-Methyl-d-Aspartate Receptor Positive Allosteric Modulator for the Potential Treatment of Cognitive Impairment. Journal of Medicinal Chemistry. 65(13). 9063–9075. 28 indexed citations

Antonoudiou, Pantelis, Grant L. Weiss, Anne C. Smith, et al.. (2021). Allopregnanolone Mediates Affective Switching Through Modulation of Oscillatory States in the Basolateral Amygdala. Biological Psychiatry. 91(3). 283–293. 75 indexed citations

Lewis, Michael, Jing Dai, Amrita Mohan, et al.. (2020). 24(S)-Hydroxycholesterol Levels are Decreased in Early Huntington’s Disease and Are Associated with Deficits in Several Cognitive Domains (4070). Neurology. 94(15_supplement). 4 indexed citations

Koenig, Aaron, Harald Murck, Yingchun Luo, et al.. (2020). Using a Multimodal Biomarker Approach to Identify Functional Target Engagement of the Novel NMDA Positive Allosteric Modulator SAGE-718 (1944). Neurology. 94(15_supplement). 1 indexed citations

Nguyen, David P., Anne C. Smith, E. Hoffman, et al.. (2020). Mechanistic PK/PD Model of Neuroactive Steroid GABAA Positive Allosteric Modulation and Effects on TETRAS Assessment in Essential Tremor (4499). Neurology. 94(15_supplement). 1 indexed citations

Benz, Ann, Hong‐Jin Shu, Steven M. Paul, et al.. (2018). Positive Allosteric Modulation as a Potential Therapeutic Strategy in Anti-NMDA Receptor Encephalitis. Journal of Neuroscience. 38(13). 3218–3229. 38 indexed citations

Sanacora, Gerard, Michael R. Johnson, Arif Khan, et al.. (2016). Adjunctive Lanicemine (AZD6765) in Patients with Major Depressive Disorder and History of Inadequate Response to Antidepressants: A Randomized, Placebo-Controlled Study. Neuropsychopharmacology. 42(4). 844–853. 89 indexed citations

10.

Sanacora, Gerard, Mark A. Smith, Sanjeev Pathak, et al.. (2013). Lanicemine: a low-trapping NMDA channel blocker produces sustained antidepressant efficacy with minimal psychotomimetic adverse effects. Molecular Psychiatry. 19(9). 978–985. 198 indexed citations

11.

Shirey, Jana K., Ashley E. Brady, Paulianda J. Jones, et al.. (2009). A Selective Allosteric Potentiator of the M₁Muscarinic Acetylcholine Receptor Increases Activity of Medial Prefrontal Cortical Neurons and Restores Impairments in Reversal Learning. Journal of Neuroscience. 29(45). 14271–14286. 199 indexed citations

12.

Sydserff, S G, Dekun Song, Michael C. Quirk, et al.. (2009). Selective α7 nicotinic receptor activation by AZD0328 enhances cortical dopamine release and improves learning and attentional processes. Biochemical Pharmacology. 78(7). 880–888. 81 indexed citations

13.

Feierstein, Claudia E., Michael C. Quirk, Naoshige Uchida, Dara L. Sosulski, & Zachary F. Mainen. (2006). Representation of Spatial Goals in Rat Orbitofrontal Cortex. Neuron. 51(4). 495–507. 196 indexed citations

14.

Sneider, Jennifer T., et al.. (2006). Differential behavioral state-dependence in the burst properties of CA3 and CA1 neurons. Neuroscience. 141(4). 1665–1677. 25 indexed citations

15.

Barbieri, Riccardo, Loren M. Frank, David P. Nguyen, et al.. (2005). A Bayesian decoding algorithm for analysis of information encoding in neural ensembles. PubMed. 4. 4483–4486. 4 indexed citations

16.

Nakazawa, Kazu, Linus D. Sun, Michael C. Quirk, et al.. (2003). Hippocampal CA3 NMDA Receptors Are Crucial for Memory Acquisition of One-Time Experience. Neuron. 38(2). 305–315. 375 indexed citations

17.

Nakazawa, Kazu, Michael C. Quirk, Raymond A. Chitwood, et al.. (2002). Requirement for Hippocampal CA3 NMDA Receptors in Associative Memory Recall. Science. 297(5579). 211–218. 802 indexed citations breakdown →

18.

Barbieri, Riccardo, Michael C. Quirk, Loren M. Frank, Matthew A. Wilson, & Emery N. Brown. (2001). Construction and analysis of non-Poisson stimulus-response models of neural spiking activity. Journal of Neuroscience Methods. 105(1). 25–37. 150 indexed citations

19.

Mehta, Mayank, Michael C. Quirk, & Matthew Wilson. (2000). Experience-Dependent Asymmetric Shape of Hippocampal Receptive Fields. Neuron. 25(3). 707–715. 355 indexed citations

20.

Quirk, Michael C. & Matthew Wilson. (1999). Interaction between spike waveform classification and temporal sequence detection. Journal of Neuroscience Methods. 94(1). 41–52. 80 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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