Pamela M. Loadman

483 total citations
8 papers, 386 citations indexed

About

Pamela M. Loadman is a scholar working on Neurology, Cognitive Neuroscience and Biomedical Engineering. According to data from OpenAlex, Pamela M. Loadman has authored 8 papers receiving a total of 386 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Neurology, 4 papers in Cognitive Neuroscience and 4 papers in Biomedical Engineering. Recurrent topics in Pamela M. Loadman's work include Muscle activation and electromyography studies (4 papers), Motor Control and Adaptation (4 papers) and Botulinum Toxin and Related Neurological Disorders (4 papers). Pamela M. Loadman is often cited by papers focused on Muscle activation and electromyography studies (4 papers), Motor Control and Adaptation (4 papers) and Botulinum Toxin and Related Neurological Disorders (4 papers). Pamela M. Loadman collaborates with scholars based in Canada, United States and Brazil. Pamela M. Loadman's co-authors include E. Paul Zehr, Sandra R. Hundza, Jaclyn E. Balter, Daniel P. Ferris, Taryn Klarner, Trevor S. Barss, Yao Sun, Marc Klimstra, Tomoyoshi Komiyama and Rinaldo A. Mezzarane and has published in prestigious journals such as The Journal of Physiology, Journal of Neurophysiology and Experimental Brain Research.

In The Last Decade

Pamela M. Loadman

8 papers receiving 379 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Pamela M. Loadman Canada	8	211	156	139	116	94	8	386
Taryn Klarner Canada	12	262 1.2×	162 1.0×	121 0.9×	133 1.1×	93 1.0×	24	476
Carlos Haridas Canada	7	296 1.4×	270 1.7×	142 1.0×	63 0.5×	68 0.7×	8	489
Rinaldo A. Mezzarane Brazil	14	280 1.3×	198 1.3×	152 1.1×	74 0.6×	65 0.7×	28	548
Hang Jin Jo United States	13	259 1.2×	245 1.6×	137 1.0×	74 0.6×	52 0.6×	21	538
Hiroki Obata Japan	15	262 1.2×	177 1.1×	164 1.2×	69 0.6×	81 0.9×	45	511
Claire F. Honeycutt United States	15	244 1.2×	358 2.3×	128 0.9×	126 1.1×	113 1.2×	29	604
R Spidalieri Italy	8	91 0.4×	85 0.5×	102 0.7×	81 0.7×	82 0.9×	9	468
Aiko Kido Canada	6	315 1.5×	207 1.3×	235 1.7×	88 0.8×	55 0.6×	7	519
Andrew James Thomas Stevenson Denmark	11	236 1.1×	319 2.0×	111 0.8×	72 0.6×	45 0.5×	24	506
Jarugool Tretriluxana Thailand	14	110 0.5×	115 0.7×	127 0.9×	196 1.7×	79 0.8×	40	419

Countries citing papers authored by Pamela M. Loadman

Since Specialization

Citations

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

Fields of papers citing papers by Pamela M. Loadman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pamela M. Loadman

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

All Works

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8 of 8 papers shown

1.

Zehr, E. Paul, Trevor S. Barss, Alain Frigon, et al.. (2016). Neuromechanical interactions between the limbs during human locomotion: an evolutionary perspective with translation to rehabilitation. Experimental Brain Research. 234(11). 3059–3081. 81 indexed citations

2.

Klarner, Taryn, et al.. (2016). Exploiting Interlimb Arm and Leg Connections for Walking Rehabilitation: A Training Intervention in Stroke. Neural Plasticity. 2016. 1–19. 33 indexed citations

3.

Klarner, Taryn, et al.. (2016). Long-Term Plasticity in Reflex Excitability Induced by Five Weeks of Arm and Leg Cycling Training after Stroke. Brain Sciences. 6(4). 54–54. 26 indexed citations

4.

Zehr, E. Paul, Pamela M. Loadman, & Sandra R. Hundza. (2012). Neural control of rhythmic arm cycling after stroke. Journal of Neurophysiology. 108(3). 891–905. 38 indexed citations

5.

Zehr, E. Paul & Pamela M. Loadman. (2011). Persistence of locomotor-related interlimb reflex networks during walking after stroke. Clinical Neurophysiology. 123(4). 796–807. 50 indexed citations

6.

Zehr, E. Paul, Sandra R. Hundza, Jaclyn E. Balter, & Pamela M. Loadman. (2009). Context-Dependent Modulation of Cutaneous Reflex Amplitudes during Forward and Backward Leg Cycling. Motor Control. 13(4). 368–386. 8 indexed citations

7.

Zehr, E. Paul, et al.. (2007). Neural regulation of rhythmic arm and leg movement is conserved across human locomotor tasks. The Journal of Physiology. 582(1). 209–227. 105 indexed citations

8.

Loadman, Pamela M. & E. Paul Zehr. (2006). Rhythmic arm cycling produces a non-specific signal that suppresses Soleus H-reflex amplitude in stationary legs. Experimental Brain Research. 179(2). 199–208. 45 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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