Michael J. Koval

533 total citations
9 papers, 403 citations indexed

About

Michael J. Koval is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology and Sensory Systems. According to data from OpenAlex, Michael J. Koval has authored 9 papers receiving a total of 403 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Cognitive Neuroscience, 2 papers in Experimental and Cognitive Psychology and 1 paper in Sensory Systems. Recurrent topics in Michael J. Koval's work include Neural and Behavioral Psychology Studies (7 papers), Neural dynamics and brain function (6 papers) and Visual perception and processing mechanisms (4 papers). Michael J. Koval is often cited by papers focused on Neural and Behavioral Psychology Studies (7 papers), Neural dynamics and brain function (6 papers) and Visual perception and processing mechanisms (4 papers). Michael J. Koval collaborates with scholars based in Canada and United States. Michael J. Koval's co-authors include Stefan Everling, Kevin Johnston, Stephen G. Lomber, Benson Thomas, Kristen A. Ford, R. Matthew Hutchison and Thilo Womelsdorf and has published in prestigious journals such as Neuron, Journal of Neuroscience and Journal of Neurophysiology.

In The Last Decade

Michael J. Koval

9 papers receiving 395 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Michael J. Koval Canada	7	372	51	39	36	27	9	403
Masako Matsuzawa Japan	8	398 1.1×	45 0.9×	37 0.9×	39 1.1×	14 0.5×	10	447
Michael A. Steinmetz United States	4	674 1.8×	36 0.7×	31 0.8×	74 2.1×	24 0.9×	4	733
Martijn G. van Koningsbruggen United Kingdom	10	341 0.9×	44 0.9×	70 1.8×	57 1.6×	26 1.0×	12	397
Avinash R. Vaidya United States	11	330 0.9×	39 0.8×	16 0.4×	70 1.9×	27 1.0×	14	404
Jordana S. Wynn Canada	9	328 0.9×	38 0.7×	13 0.3×	36 1.0×	22 0.8×	16	380
Luca Iemi Germany	8	634 1.7×	80 1.6×	24 0.6×	61 1.7×	31 1.1×	9	652
M. Gabriela Costello United States	10	372 1.0×	91 1.8×	19 0.5×	33 0.9×	44 1.6×	12	438
Nelly Amador United States	5	558 1.5×	99 1.9×	71 1.8×	38 1.1×	23 0.9×	6	609
Masashi Koizumi Japan	8	458 1.2×	135 2.6×	18 0.5×	29 0.8×	23 0.9×	11	526
Adam N. Phillips Japan	6	356 1.0×	63 1.2×	10 0.3×	26 0.7×	29 1.1×	6	394

Countries citing papers authored by Michael J. Koval

Since Specialization

Citations

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

Fields of papers citing papers by Michael J. Koval

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael J. Koval

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

All Works

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9 of 9 papers shown

Koval, Michael J., et al.. (2017). Neural correlates for task switching in the macaque superior colliculus. Journal of Neurophysiology. 118(4). 2156–2170. 6 indexed citations

Koval, Michael J., et al.. (2014). Dorsolateral Prefrontal Cortex Deactivation in Monkeys Reduces Preparatory Beta and Gamma Power in the Superior Colliculus. Cerebral Cortex. 25(12). 4704–4714. 9 indexed citations

Johnston, Kevin, Michael J. Koval, Stephen G. Lomber, & Stefan Everling. (2013). Macaque Dorsolateral Prefrontal Cortex Does not Suppress Saccade-Related Activity in the Superior Colliculus. Cerebral Cortex. 24(5). 1373–1388. 48 indexed citations

Koval, Michael J., R. Matthew Hutchison, Stephen G. Lomber, & Stefan Everling. (2013). Effects of unilateral deactivations of dorsolateral prefrontal cortex and anterior cingulate cortex on saccadic eye movements. Journal of Neurophysiology. 111(4). 787–803. 16 indexed citations

Koval, Michael J.. (2012). An Investigation of the Neural Mechanism by which the Prefrontal Cortex Facilitates Anti-saccade Task Performance. Scholarship@Western (Western University). 1 indexed citations

Koval, Michael J., Stephen G. Lomber, & Stefan Everling. (2011). Prefrontal Cortex Deactivation in Macaques Alters Activity in the Superior Colliculus and Impairs Voluntary Control of Saccades. Journal of Neuroscience. 31(23). 8659–8668. 45 indexed citations

Johnston, Kevin, et al.. (2007). Top-Down Control-Signal Dynamics in Anterior Cingulate and Prefrontal Cortex Neurons following Task Switching. Neuron. 53(3). 453–462. 228 indexed citations

Koval, Michael J., Benson Thomas, & Stefan Everling. (2005). Task-dependent effects of social attention on saccadic reaction times. Experimental Brain Research. 167(3). 475–480. 30 indexed citations

Koval, Michael J., Kristen A. Ford, & Stefan Everling. (2004). Effect of stimulus probability on anti-saccade error rates. Experimental Brain Research. 159(2). 268–272. 20 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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