Heather M. Shappell

908 total citations
25 papers, 480 citations indexed

About

Heather M. Shappell is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology and Psychiatry and Mental health. According to data from OpenAlex, Heather M. Shappell has authored 25 papers receiving a total of 480 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Cognitive Neuroscience, 5 papers in Experimental and Cognitive Psychology and 5 papers in Psychiatry and Mental health. Recurrent topics in Heather M. Shappell's work include Functional Brain Connectivity Studies (11 papers), Neural dynamics and brain function (5 papers) and Mental Health Research Topics (5 papers). Heather M. Shappell is often cited by papers focused on Functional Brain Connectivity Studies (11 papers), Neural dynamics and brain function (5 papers) and Mental Health Research Topics (5 papers). Heather M. Shappell collaborates with scholars based in United States, Canada and Japan. Heather M. Shappell's co-authors include Ralph B. D’Agostino, Susan Campbell, Mark W. Kieran, Monica E. Kleinman, Joan F. Brazier, Leslie B. Gordon, Joseph M. Massaro, Martin A. Lindquist, James J. Pekar and Ellen Matloff and has published in prestigious journals such as JAMA, Journal of Clinical Oncology and NeuroImage.

In The Last Decade

Heather M. Shappell

19 papers receiving 469 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Heather M. Shappell United States 10 162 111 89 51 40 25 480
Justin T. Wahlstrom United States 11 132 0.8× 172 1.5× 37 0.4× 35 0.7× 33 0.8× 29 616
Jennifer Su United States 7 114 0.7× 55 0.5× 59 0.7× 42 0.8× 16 0.4× 14 392
John D. Eicher United States 13 172 1.1× 189 1.7× 84 0.9× 27 0.5× 30 0.8× 18 668
Sara Moruzzi Italy 13 321 2.0× 76 0.7× 68 0.8× 41 0.8× 67 1.7× 32 614
Fahad A. Bashiri Saudi Arabia 12 131 0.8× 96 0.9× 45 0.5× 76 1.5× 93 2.3× 63 552
Dora Janeth Fonseca Colombia 13 133 0.8× 101 0.9× 31 0.3× 55 1.1× 62 1.6× 65 457
Shao‐Yin Chu Taiwan 13 128 0.8× 119 1.1× 43 0.5× 54 1.1× 59 1.5× 52 491
Leanne Wallace Australia 13 118 0.7× 130 1.2× 34 0.4× 39 0.8× 27 0.7× 21 591
Jeff Gregg United States 12 233 1.4× 135 1.2× 148 1.7× 18 0.4× 33 0.8× 15 715
Biruté Tumiene Lithuania 13 81 0.5× 142 1.3× 28 0.3× 34 0.7× 46 1.1× 25 363

Countries citing papers authored by Heather M. Shappell

Since Specialization
Citations

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

Fields of papers citing papers by Heather M. Shappell

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Heather M. Shappell

This figure shows the co-authorship network connecting the top 25 collaborators of Heather M. Shappell. A scholar is included among the top collaborators of Heather M. Shappell 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 Heather M. Shappell. Heather M. Shappell 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.
Mielke, Michelle M., Joni K. Evans, Rebecca H. Neiberg, et al.. (2025). Alzheimer Disease Blood Biomarkers and Cognition Among Individuals With Diabetes and Overweight or Obesity. JAMA Network Open. 8(2). e2458149–e2458149. 7 indexed citations
2.
Lyday, Robert G., et al.. (2025). Triple network dynamics and future alcohol consumption in adolescents. Alcohol Clinical and Experimental Research. 49(6). 1206–1220. 1 indexed citations
3.
Jia, Wei, Go Eun Lee, Heather M. Shappell, et al.. (2025). Transdiagnostic Symptom Domains Have Distinct Patterns of Association With Head Motion During Multimodal Imaging in Children. Biological Psychiatry Global Open Science. 5(4). 100506–100506. 1 indexed citations
4.
Lyday, Robert G., et al.. (2025). Fractal Analysis of Brain Activity During Risky Drinking in Adolescents and Young Adults. Brain Sciences. 15(12). 1256–1256.
5.
Shappell, Heather M., W. Jack Rejeski, Robert G. Lyday, et al.. (2025). Brain network dynamics associated with intentional weight loss in older adults. PubMed. 5.
6.
Shappell, Heather M., et al.. (2024). Contrasting topologies of synchronous and asynchronous functional brain networks. Network Neuroscience. 8(4). 1–16.
7.
Hayden, Kathleen M., Michelle M. Mielke, Rebecca H. Neiberg, et al.. (2024). Association between Modifiable Risk Factors and Levels of Blood-Based Biomarkers of Alzheimer's and Related Dementias in the Look AHEAD Cohort. PubMed. 13. 1–21. 11 indexed citations
8.
Sachs, Bonnie C., Mark A. Espeland, Eric S. Fischer, et al.. (2024). Feasibility of Remote Administration of the Uniform Data Set-Version 3 for Assessment of Older Adults With Mild Cognitive Impairment and Alzheimer’s Disease. Archives of Clinical Neuropsychology. 39(5). 635–643. 4 indexed citations
9.
Shappell, Heather M., et al.. (2023). Distinguishing between different percolation regimes in noisy dynamic networks with an application to epileptic seizures. PLoS Computational Biology. 19(6). e1011188–e1011188. 1 indexed citations
10.
11.
Simpson, Sean L., et al.. (2023). Statistical Brain Network Analysis. Annual Review of Statistics and Its Application. 11(1). 505–531.
12.
Laurienti, Paul J., et al.. (2022). A mixed-modeling framework for whole-brain dynamic network analysis. Network Neuroscience. 6(2). 591–613. 7 indexed citations
13.
Laurienti, Paul J., et al.. (2022). Brain Network Analysis: A Review on Multivariate Analytical Methods. Brain Connectivity. 13(2). 64–79. 6 indexed citations
14.
15.
Sarhane, Karim A., Benjamin R. Slavin, Harsha Malapati, et al.. (2021). Defining the relative impact of muscle versus Schwann cell denervation on functional recovery after delayed nerve repair. Experimental Neurology. 339. 113650–113650. 12 indexed citations
16.
Shappell, Heather M., Brian Caffo, James J. Pekar, & Martin A. Lindquist. (2019). Improved state change estimation in dynamic functional connectivity using hidden semi-Markov models. NeuroImage. 191. 243–257. 38 indexed citations
17.
Maru, Mihoko, E. Sally Rogers, Dori S. Hutchinson, & Heather M. Shappell. (2018). An Integrated Supported Employment and Education Model: Exploratory Study of an Innovative Approach Designed to Better Meet the Needs of Young Adults with Psychiatric Conditions. The Journal of Behavioral Health Services & Research. 45(3). 489–498. 4 indexed citations
18.
Burke, Gordon M., Michael V. Genuardi, Heather M. Shappell, Ralph B. D’Agostino, & Jared W. Magnani. (2017). Temporal Associations Between Smoking and Cardiovascular Disease, 1971 to 2006 (from the Framingham Heart Study). The American Journal of Cardiology. 120(10). 1787–1791. 33 indexed citations
19.
Sebastiani, Paola, John J. Farrell, Heather M. Shappell, et al.. (2015). BCL11A enhancer haplotypes and fetal hemoglobin in sickle cell anemia. Blood Cells Molecules and Diseases. 54(3). 224–230. 32 indexed citations
20.
Sutphen, Rebecca, Heather M. Shappell, Susan T. Vadaparampil, et al.. (2010). Real world experience with cancer genetic counseling via telephone. Familial Cancer. 9(4). 681–689. 34 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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