Maria C. Dadarlat

587 total citations
9 papers, 304 citations indexed

About

Maria C. Dadarlat is a scholar working on Cellular and Molecular Neuroscience, Cognitive Neuroscience and Electrical and Electronic Engineering. According to data from OpenAlex, Maria C. Dadarlat has authored 9 papers receiving a total of 304 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Cellular and Molecular Neuroscience, 8 papers in Cognitive Neuroscience and 4 papers in Electrical and Electronic Engineering. Recurrent topics in Maria C. Dadarlat's work include Neuroscience and Neural Engineering (7 papers), Neural dynamics and brain function (5 papers) and EEG and Brain-Computer Interfaces (4 papers). Maria C. Dadarlat is often cited by papers focused on Neuroscience and Neural Engineering (7 papers), Neural dynamics and brain function (5 papers) and EEG and Brain-Computer Interfaces (4 papers). Maria C. Dadarlat collaborates with scholars based in United States and United Kingdom. Maria C. Dadarlat's co-authors include Michael P. Stryker, Philip N. Sabes, Joseph E. O’Doherty, Yujiao Jennifer Sun, Amy L. Orsborn, Steven W. Zucker, Sabrina S. Jedlicka, Min Zhang, Pedro P. Irazoqui and Jenna L. Rickus and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Neuron and Journal of Neuroscience.

In The Last Decade

Maria C. Dadarlat

9 papers receiving 304 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Maria C. Dadarlat United States	7	269	199	42	35	21	9	304
Heiko Stemmann Germany	10	222 0.8×	135 0.7×	54 1.3×	58 1.7×	9 0.4×	19	317
Jay A. Hennig United States	7	301 1.1×	99 0.5×	29 0.7×	18 0.5×	9 0.4×	9	326
Katia Galan Switzerland	6	205 0.8×	214 1.1×	53 1.3×	25 0.7×	17 0.8×	6	342
Cem Uran Germany	9	356 1.3×	185 0.9×	13 0.3×	25 0.7×	21 1.0×	11	392
Maureen A. Hagan Australia	10	288 1.1×	117 0.6×	18 0.4×	25 0.7×	17 0.8×	27	321
Christian Waiblinger United States	9	287 1.1×	218 1.1×	17 0.4×	12 0.3×	40 1.9×	12	336
Ruiqing Hou China	5	244 0.9×	295 1.5×	55 1.3×	92 2.6×	31 1.5×	10	415
Chie Matsubara Japan	5	312 1.2×	214 1.1×	19 0.5×	26 0.7×	17 0.8×	8	396
Whitney S. Griggs United States	10	240 0.9×	96 0.5×	39 0.9×	14 0.4×	19 0.9×	12	329
Sean M. Perkins United States	5	287 1.1×	85 0.4×	68 1.6×	20 0.6×	7 0.3×	7	318

Countries citing papers authored by Maria C. Dadarlat

Since Specialization

Citations

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

Fields of papers citing papers by Maria C. Dadarlat

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Maria C. Dadarlat. 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 Maria C. Dadarlat. The network helps show where Maria C. Dadarlat may publish in the future.

Co-authorship network of co-authors of Maria C. Dadarlat

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

All Works

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9 of 9 papers shown

Dadarlat, Maria C., Yujiao Jennifer Sun, & Michael P. Stryker. (2023). Activity-dependent recruitment of inhibition and excitation in the awake mammalian cortex during electrical stimulation. Neuron. 112(5). 821–834.e4. 14 indexed citations

Dadarlat, Maria C., et al.. (2023). Neural Plasticity in Sensorimotor Brain–Machine Interfaces. Annual Review of Biomedical Engineering. 25(1). 51–76. 11 indexed citations

Dadarlat, Maria C., Yujiao Jennifer Sun, & Michael P. Stryker. (2019). Widespread activation of awake mouse cortex by electrical stimulation. PubMed. 2019. 1113–1117. 8 indexed citations

Dadarlat, Maria C., et al.. (2018). Flow stimuli reveal ecologically appropriate responses in mouse visual cortex. Proceedings of the National Academy of Sciences. 115(44). 11304–11309. 14 indexed citations

Dadarlat, Maria C. & Michael P. Stryker. (2017). Locomotion Enhances Neural Encoding of Visual Stimuli in Mouse V1. Journal of Neuroscience. 37(14). 3764–3775. 109 indexed citations

Dadarlat, Maria C. & Philip N. Sabes. (2016). Encoding and Decoding of Multi-Channel ICMS in Macaque Somatosensory Cortex. IEEE Transactions on Haptics. 9(4). 508–514. 2 indexed citations

Sabes, Philip N., Maria C. Dadarlat, & Joseph E. O’Doherty. (2015). A learning-based approach to artificial sensory feedback. 3782–3782. 2 indexed citations

Dadarlat, Maria C., Joseph E. O’Doherty, & Philip N. Sabes. (2014). A learning-based approach to artificial sensory feedback leads to optimal integration. Nature Neuroscience. 18(1). 138–144. 138 indexed citations

Jedlicka, Sabrina S., Maria C. Dadarlat, Yanzhu Lin, et al.. (2009). CALIBRATION OF NEUROTRANSMITTER RELEASE FROM NEURAL CELLS FOR THERAPEUTIC IMPLANTS. International Journal of Neural Systems. 19(3). 197–212. 6 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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