Danielle M. Williams
- Cognitive Neuroscience top 5%
- Experimental and Cognitive Psychology top 10%
- Psychiatry and Mental health
- Social Psychology
- Radiology, Nuclear Medicine and Imaging
- Co-authors
- Christopher I. WrightEric FeczkoPhillip J. HolcombKirk R. DaffnerBradford DickersonAndrew E. BudsonDorene M. RentzHyemi Chong
- Topics
- Neural and Behavioral Psychology Studies (8 papers)Neural dynamics and brain function (4 papers)Functional Brain Connectivity Studies (3 papers)
- Cited by
- Neuropsychology and Physiological PsychologyCognitive NeuroscienceExperimental and Cognitive Psychology
- Partner nations
- United StatesAustralia
In The Last Decade
Danielle M. Williams
12 papers receiving 459 citations
Peers
Comparison fields: 5 of 62
- Cognitive Neuroscience 369
- Experimental and Cognitive Psychology 108
- Psychiatry and Mental health 78
- Social Psychology 48
- Radiology, Nuclear Medicine and Imaging 39
Countries citing papers authored by Danielle M. Williams
This map shows the geographic impact of Danielle M. Williams'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 Danielle M. Williams with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Danielle M. Williams more than expected).
Fields of papers citing papers by Danielle M. Williams
This network shows the impact of papers produced by Danielle M. Williams. 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 Danielle M. Williams. The network helps show where Danielle M. Williams may publish in the future.
Co-authorship network of co-authors of Danielle M. Williams
This figure shows the co-authorship network connecting the top 25 collaborators of Danielle M. Williams. A scholar is included among the top collaborators of Danielle M. Williams 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 Danielle M. Williams. Danielle M. Williams is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | Approaching the (Re)Design of Writing Majors: Contexts of Research, Forms of Inquiry, and Recommendations for Faculty. | 1 |
| 3 | 9 | |
| 4 | 54 | |
| 5 | 83 | |
| 6 | 74 | |
| 7 | 43 | |
| 8 | 47 | |
| 9 | 60 | |
| 10 | 35 | |
| 11 | 3 | |
| 12 | 27 | |
| 13 | 34 |
About Danielle M. Williams
Danielle M. Williams is a scholar working on Neuropsychology and Physiological Psychology, Cognitive Neuroscience and Literature and Literary Theory, having authored 13 papers that have together received 470 indexed citations. Recurring topics across this work include Neural and Behavioral Psychology Studies (8 papers), Neural dynamics and brain function (4 papers) and Functional Brain Connectivity Studies (3 papers). The work is most often cited by research in Neuropsychology and Physiological Psychology (33 citations), Cognitive Neuroscience (369 citations) and Experimental and Cognitive Psychology (108 citations). Danielle M. Williams has collaborated with scholars based in United States and Australia. Frequent co-authors include Christopher I. Wright, Eric Feczko, Phillip J. Holcomb, Kirk R. Daffner, Bradford Dickerson, Andrew E. Budson, Dorene M. Rentz, Hyemi Chong, Scott M. McGinnis and Bradford C. Dickerson. Their work appears in journals such as NeuroImage, Biological Psychiatry and Journal of Cognitive Neuroscience.
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.