Darlene V. Howard

6.6k total citations
92 papers, 5.0k citations indexed

About

Darlene V. Howard is a scholar working on Cognitive Neuroscience, Developmental and Educational Psychology and Social Psychology. According to data from OpenAlex, Darlene V. Howard has authored 92 papers receiving a total of 5.0k indexed citations (citations by other indexed papers that have themselves been cited), including 64 papers in Cognitive Neuroscience, 43 papers in Developmental and Educational Psychology and 19 papers in Social Psychology. Recurrent topics in Darlene V. Howard's work include Child and Animal Learning Development (28 papers), Neural and Behavioral Psychology Studies (21 papers) and Action Observation and Synchronization (19 papers). Darlene V. Howard is often cited by papers focused on Child and Animal Learning Development (28 papers), Neural and Behavioral Psychology Studies (21 papers) and Action Observation and Synchronization (19 papers). Darlene V. Howard collaborates with scholars based in United States, Hungary and Italy. Darlene V. Howard's co-authors include James H. Howard, Chandan J. Vaidya, Ilana J. Bennett, James H. Howard, Sunbin Song, David J. Madden, Sharon A. Mutter, Nancy A. Dennis, Mary Pat McAndrews and Guinevere F. Eden and has published in prestigious journals such as Journal of Clinical Oncology, Journal of Neuroscience and PLoS ONE.

In The Last Decade

Darlene V. Howard

92 papers receiving 4.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Darlene V. Howard United States 43 3.7k 1.8k 917 616 495 92 5.0k
Gabriele Miceli Italy 37 4.1k 1.1× 2.7k 1.5× 504 0.5× 821 1.3× 400 0.8× 132 5.0k
Mary Jo Nissen United States 29 4.5k 1.2× 1.8k 1.0× 1.5k 1.7× 1.1k 1.7× 429 0.9× 41 6.8k
Anna Basso Italy 33 2.9k 0.8× 1.0k 0.6× 519 0.6× 437 0.7× 508 1.0× 84 3.6k
Stefan Heim Germany 31 2.6k 0.7× 1.5k 0.8× 425 0.5× 586 1.0× 383 0.8× 121 3.7k
Franco Fabbro Italy 42 2.9k 0.8× 1.4k 0.8× 1.2k 1.3× 850 1.4× 699 1.4× 193 5.5k
Jenny Crinion United Kingdom 38 4.5k 1.2× 1.6k 0.9× 435 0.5× 622 1.0× 507 1.0× 76 5.3k
Claudio Luzzatti Italy 33 3.6k 1.0× 1.5k 0.9× 537 0.6× 575 0.9× 313 0.6× 144 4.3k
Anna Berti Italy 34 6.5k 1.8× 904 0.5× 1.6k 1.7× 908 1.5× 1.1k 2.3× 115 8.3k
Ayşe Pınar Saygın United States 30 3.8k 1.0× 888 0.5× 1.8k 1.9× 1.2k 2.0× 378 0.8× 62 5.2k
Brenda Rapp United States 41 4.5k 1.2× 3.3k 1.8× 480 0.5× 999 1.6× 270 0.5× 158 5.5k

Countries citing papers authored by Darlene V. Howard

Since Specialization
Citations

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

Fields of papers citing papers by Darlene V. Howard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Darlene V. Howard. 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 Darlene V. Howard. The network helps show where Darlene V. Howard may publish in the future.

Co-authorship network of co-authors of Darlene V. Howard

This figure shows the co-authorship network connecting the top 25 collaborators of Darlene V. Howard. A scholar is included among the top collaborators of Darlene V. Howard 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 Darlene V. Howard. Darlene V. Howard 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.
Jiang, Xiong, et al.. (2017). Individual Differences in Cognitive Function in Older Adults Predicted by Neuronal Selectivity at Corresponding Brain Regions. Frontiers in Aging Neuroscience. 9. 103–103. 15 indexed citations
2.
Seaman, Kendra Leigh, Chelsea M. Stillman, Darlene V. Howard, & James H. Howard. (2015). Risky decision-making is associated with residential choice in healthy older adults. Frontiers in Psychology. 6. 1192–1192. 10 indexed citations
3.
Mandelblatt, Jeanne S., Robert A. Stern, George Luta, et al.. (2014). Cognitive impairment in older patients with breast cancer before systemic therapy: is there an interaction between cancer and comorbidity?. PMC. 1 indexed citations
4.
Cummings, Thomas J., et al.. (2014). Implicit sequence learning in people with Parkinson’s disease. Frontiers in Human Neuroscience. 8. 563–563. 18 indexed citations
5.
Seaman, Kendra Leigh, Darlene V. Howard, & James H. Howard. (2014). Adult age differences in subjective and objective measures of strategy use on a sequentially cued prediction task. Aging Neuropsychology and Cognition. 22(2). 170–182. 5 indexed citations
6.
Seaman, Kendra Leigh, et al.. (2014). Event Simultaneity Does Not Eliminate Age Deficits in Implicit Probabilistic Sequence Learning. The International Journal of Aging and Human Development. 79(3). 211–223. 1 indexed citations
7.
Stillman, Chelsea M., et al.. (2013). Caudate Resting Connectivity Predicts Implicit Probabilistic Sequence Learning. Brain Connectivity. 3(6). 601–610. 31 indexed citations
8.
Mandelblatt, Jeanne S., Arti Hurria, Brenna C. McDonald, et al.. (2013). Cognitive effects of cancer and its treatments at the intersection of aging: what do we know; what do we need to know?. PMC. 1 indexed citations
9.
Howard, James H. & Darlene V. Howard. (2013). Aging mind and brain: is implicit learning spared in healthy aging?. Frontiers in Psychology. 4. 817–817. 67 indexed citations
10.
Mandelblatt, Jeanne S., Arti Hurria, Brenna C. McDonald, et al.. (2013). Cognitive Effects of Cancer and Its Treatments at the Intersection of Aging: What Do We Know; What Do We Need to Know?. Seminars in Oncology. 40(6). 709–725. 112 indexed citations
11.
Howard, James H., et al.. (2013). Does a simultaneous memory load affect older and younger adults’ implicit associative learning?. Aging Neuropsychology and Cognition. 21(1). 52–67. 9 indexed citations
12.
Howard, James H., et al.. (2011). Enhanced Implicit Sequence Learning in College‐age Video Game Players and Musicians. Applied Cognitive Psychology. 26(1). 91–96. 51 indexed citations
13.
Stollstorff, Melanie, et al.. (2010). Dopamine transporter genotype predicts implicit sequence learning. Behavioural Brain Research. 216(1). 452–457. 30 indexed citations
14.
Dennis, Nancy A., James H. Howard, & Darlene V. Howard. (2006). Implicit sequence learning without motor sequencing in young and old adults. Experimental Brain Research. 175(1). 153–164. 77 indexed citations
15.
Howard, Darlene V., et al.. (1997). Age differences in implicit learning of higher order dependencies in serial patterns.. Psychology and Aging. 12(4). 634–656. 14 indexed citations
16.
Howard, Darlene V. & James H. Howard. (1992). Adult age differences in the rate of learning serial patterns: Evidence from direct and indirect tests.. Psychology and Aging. 7(2). 232–241. 128 indexed citations
17.
Howard, James H., Sharon A. Mutter, & Darlene V. Howard. (1992). Serial pattern learning by event observation.. Journal of Experimental Psychology Learning Memory and Cognition. 18(5). 1029–1039. 80 indexed citations
18.
Howard, Darlene V.. (1985). Aging and Episodic Priming: The Propositional Structure of Sentences.. 2 indexed citations
19.
Howard, Darlene V. & Deborah M. Burke. (1983). Aging and the Semantic Priming of Lexical Decisions.. 2 indexed citations
20.
Howard, Darlene V.. (1976). Search and decision processes in intentional forgetting: A reaction time analysis.. Journal of Experimental Psychology Human Learning & Memory. 2(5). 566–576. 1 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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