William J. Kargo

1.2k total citations
18 papers, 889 citations indexed

About

William J. Kargo is a scholar working on Cognitive Neuroscience, Biomedical Engineering and Cellular and Molecular Neuroscience. According to data from OpenAlex, William J. Kargo has authored 18 papers receiving a total of 889 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Cognitive Neuroscience, 10 papers in Biomedical Engineering and 6 papers in Cellular and Molecular Neuroscience. Recurrent topics in William J. Kargo's work include Muscle activation and electromyography studies (9 papers), Motor Control and Adaptation (8 papers) and Neural dynamics and brain function (4 papers). William J. Kargo is often cited by papers focused on Muscle activation and electromyography studies (9 papers), Motor Control and Adaptation (8 papers) and Neural dynamics and brain function (4 papers). William J. Kargo collaborates with scholars based in United States. William J. Kargo's co-authors include Simon F. Giszter, Douglas A. Nitz, Lawrence C. Rome, Frank E. Nelson, Arun Ramakrishnan, Corey B. Hart, Harmon Zuccola, Weichao Chen, Azin Nezami and Beth A. Fleck and has published in prestigious journals such as Journal of Neuroscience, Journal of Neurophysiology and Annals of the New York Academy of Sciences.

In The Last Decade

William J. Kargo

18 papers receiving 861 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
William J. Kargo United States 13 566 488 146 102 99 18 889
Sergiy Yakovenko United States 16 546 1.0× 577 1.2× 135 0.9× 211 2.1× 133 1.3× 38 977
C. Perret France 15 330 0.6× 322 0.7× 252 1.7× 47 0.5× 117 1.2× 23 887
Katinka Stecina Canada 16 354 0.6× 304 0.6× 227 1.6× 54 0.5× 252 2.5× 26 924
David A. McVea Canada 13 623 1.1× 180 0.4× 381 2.6× 68 0.7× 60 0.6× 19 860
G. E. Loeb United States 7 372 0.7× 435 0.9× 117 0.8× 25 0.2× 24 0.2× 12 649
Shik Ml 10 370 0.7× 315 0.6× 293 2.0× 56 0.5× 180 1.8× 40 1.0k
G. N. Orlovskiĭ Russia 9 184 0.3× 200 0.4× 115 0.8× 43 0.4× 65 0.7× 25 546
J.‐M. Cabelguen France 14 191 0.3× 268 0.5× 262 1.8× 13 0.1× 109 1.1× 18 755
J. van der Burg Netherlands 11 337 0.6× 137 0.3× 317 2.2× 25 0.2× 100 1.0× 14 867
Orlovskiĭ Gn 12 428 0.8× 328 0.7× 325 2.2× 62 0.6× 178 1.8× 36 1.1k

Countries citing papers authored by William J. Kargo

Since Specialization
Citations

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

Fields of papers citing papers by William J. Kargo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of William J. Kargo

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

All Works

18 of 18 papers shown
1.
Ernst, Justin T., Michael C. Liu, Samuel Sperry, et al.. (2014). Identification of Novel HSP90α/β Isoform Selective Inhibitors Using Structure-Based Drug Design. Demonstration of Potential Utility in Treating CNS Disorders such as Huntington’s Disease. Journal of Medicinal Chemistry. 57(8). 3382–3400. 55 indexed citations
2.
Kargo, William J., Arun Ramakrishnan, Corey B. Hart, Lawrence C. Rome, & Simon F. Giszter. (2009). A Simple Experimentally Based Model Using Proprioceptive Regulation of Motor Primitives Captures Adjusted Trajectory Formation in Spinal Frogs. Journal of Neurophysiology. 103(1). 573–590. 58 indexed citations
3.
Giszter, Simon F., et al.. (2008). Trunk Sensorimotor Cortex Is Essential for Autonomous Weight-Supported Locomotion in Adult Rats Spinalized as P1/P2 Neonates. Journal of Neurophysiology. 100(2). 839–851. 25 indexed citations
4.
Kargo, William J. & Simon F. Giszter. (2008). Individual Premotor Drive Pulses, Not Time-Varying Synergies, Are the Units of Adjustment for Limb Trajectories Constructed in Spinal Cord. Journal of Neuroscience. 28(10). 2409–2425. 74 indexed citations
5.
Nitz, Douglas A., William J. Kargo, & Jason Fleischer. (2007). Dopamine signaling and the distal reward problem. Neuroreport. 18(17). 1833–1836. 7 indexed citations
6.
Kargo, William J., et al.. (2007). Adaptation of Prefrontal Cortical Firing Patterns and Their Fidelity to Changes in Action–Reward Contingencies. Journal of Neuroscience. 27(13). 3548–3559. 43 indexed citations
7.
Kargo, William J. & Douglas A. Nitz. (2004). Improvements in the Signal-to-Noise Ratio of Motor Cortex Cells Distinguish Early versus Late Phases of Motor Skill Learning. Journal of Neuroscience. 24(24). 5560–5569. 73 indexed citations
8.
Kargo, William J. & Douglas A. Nitz. (2003). Early Skill Learning Is Expressed through Selection and Tuning of Cortically Represented Muscle Synergies. Journal of Neuroscience. 23(35). 11255–11269. 121 indexed citations
9.
Kargo, William J., Frank E. Nelson, & Lawrence C. Rome. (2002). Jumping in frogs: assessing the design of the skeletal system by anatomically realistic modeling and forward dynamic simulation. Journal of Experimental Biology. 205(12). 1683–1702. 66 indexed citations
10.
Giszter, Simon F. & William J. Kargo. (2002). Separation and estimation of muscle spindle and tension receptor populations by vibration of the biceps muscle in the frog.. PubMed. 140(4). 283–94. 6 indexed citations
11.
Kargo, William J. & Lawrence C. Rome. (2002). Functional morphology of proximal hindlimb muscles in the frogRana pipiens. Journal of Experimental Biology. 205(14). 1987–2004. 80 indexed citations
12.
Giszter, Simon F. & William J. Kargo. (2001). Modeling of dynamic controls in the frog wiping reflex: Force-field level controls. Neurocomputing. 38-40. 1239–1247. 9 indexed citations
13.
Kargo, William J. & Simon F. Giszter. (2000). Afferent Roles in Hindlimb Wipe-Reflex Trajectories: Free-Limb Kinematics and Motor Patterns. Journal of Neurophysiology. 83(3). 1480–1501. 54 indexed citations
14.
Giszter, Simon F. & William J. Kargo. (2000). Conserved temporal dynamics and vector superposition of primitives in frog wiping reflexes during spontaneous extensor deletions. Neurocomputing. 32-33. 775–783. 31 indexed citations
15.
Kargo, William J. & Simon F. Giszter. (2000). Rapid Correction of Aimed Movements by Summation of Force-Field Primitives. Journal of Neuroscience. 20(1). 409–426. 135 indexed citations
16.
Giszter, Simon F., et al.. (1998). Pattern Generators and Cortical Maps in Locomotion of Spinal Injured Ratsa. Annals of the New York Academy of Sciences. 860(1). 554–555. 8 indexed citations
17.
Kargo, William J., et al.. (1998). Segmental Afferent Regulation of Hindlimb Wiping in the Spinal Frog. Annals of the New York Academy of Sciences. 860(1). 456–457. 3 indexed citations
18.
Giszter, Simon F., et al.. (1998). Fetal Transplants Rescue Axial Muscle Representations in M1 Cortex of Neonatally Transected Rats That Develop Weight Support. Journal of Neurophysiology. 80(6). 3021–3030. 41 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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