Ralph‐Axel Müller

8.2k total citations
107 papers, 5.8k citations indexed

About

Ralph‐Axel Müller is a scholar working on Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging and Psychiatry and Mental health. According to data from OpenAlex, Ralph‐Axel Müller has authored 107 papers receiving a total of 5.8k indexed citations (citations by other indexed papers that have themselves been cited), including 93 papers in Cognitive Neuroscience, 34 papers in Radiology, Nuclear Medicine and Imaging and 29 papers in Psychiatry and Mental health. Recurrent topics in Ralph‐Axel Müller's work include Autism Spectrum Disorder Research (58 papers), Functional Brain Connectivity Studies (54 papers) and Advanced Neuroimaging Techniques and Applications (32 papers). Ralph‐Axel Müller is often cited by papers focused on Autism Spectrum Disorder Research (58 papers), Functional Brain Connectivity Studies (54 papers) and Advanced Neuroimaging Techniques and Applications (32 papers). Ralph‐Axel Müller collaborates with scholars based in United States, Germany and Japan. Ralph‐Axel Müller's co-authors include Brandon Keehn, Patricia Shih, D. K. Shukla, Aarti Nair, Inna Fishman, Christopher L. Keown, Jeanne Townsend, Michael Datko, Alan J. Lincoln and Afrooz Jahedi and has published in prestigious journals such as SHILAP Revista de lepidopterología, NeuroImage and Brain.

In The Last Decade

Ralph‐Axel Müller

102 papers receiving 5.6k citations

Peers

Ralph‐Axel Müller
Rajesh K. Kana United States
Christine Ecker United Kingdom
Mônica Zilbovicius France
Natacha Akshoomoff United States
Elizabeth Redcay United States
Ruth A. Carper United States
Dene Robertson United Kingdom
Catherine J. Stoodley United States
Janet E. Lainhart United States
François Lalonde United States
Rajesh K. Kana United States
Ralph‐Axel Müller
Citations per year, relative to Ralph‐Axel Müller Ralph‐Axel Müller (= 1×) peers Rajesh K. Kana

Countries citing papers authored by Ralph‐Axel Müller

Since Specialization
Citations

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

Fields of papers citing papers by Ralph‐Axel Müller

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ralph‐Axel Müller. 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 Ralph‐Axel Müller. The network helps show where Ralph‐Axel Müller may publish in the future.

Co-authorship network of co-authors of Ralph‐Axel Müller

This figure shows the co-authorship network connecting the top 25 collaborators of Ralph‐Axel Müller. A scholar is included among the top collaborators of Ralph‐Axel Müller 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 Ralph‐Axel Müller. Ralph‐Axel Müller 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.
Keehn, R. Joanne Jao, Michael A. Olson, Lisa E. Mash, et al.. (2024). Increased heterogeneity and task-related reconfiguration of functional connectivity during a lexicosemantic task in autism. NeuroImage Clinical. 44. 103694–103694. 1 indexed citations
2.
Linke, Annika C., Mikaela Kinnear, Alan J. Lincoln, et al.. (2024). Associations between atypical intracortical myelin content and neuropsychological functions in middle to older aged adults with ASD. Brain and Behavior. 14(6). e3594–e3594. 1 indexed citations
3.
Fan, Juanjuan, et al.. (2023). Assessing Predictive Ability of Dynamic Time Warping Functional Connectivity for ASD Classification. International Journal of Biomedical Imaging. 2023. 1–13. 3 indexed citations
4.
Hau, Janice, R. Joanne Jao Keehn, Annika C. Linke, et al.. (2022). Reduced asymmetry of the hand knob area and decreased sensorimotor u-fiber connectivity in middle-aged adults with autism. Cortex. 153. 110–125. 5 indexed citations
5.
Linke, Annika C., Lisa E. Mash, Mikaela Kinnear, et al.. (2020). Dynamic time warping outperforms Pearson correlation in detecting atypical functional connectivity in autism spectrum disorders. NeuroImage. 223. 117383–117383. 29 indexed citations
6.
Keehn, R. Joanne Jao, et al.. (2020). Underconnectivity Between Visual and Salience Networks and Links With Sensory Abnormalities in Autism Spectrum Disorders. Journal of the American Academy of Child & Adolescent Psychiatry. 60(2). 274–285. 21 indexed citations
7.
Mash, Lisa E., Brandon Keehn, Annika C. Linke, et al.. (2019). Atypical Relationships Between Spontaneous EEG and fMRI Activity in Autism. Brain Connectivity. 10(1). 18–28. 25 indexed citations
8.
Jahedi, Afrooz, Christopher Fong, Ruth A. Carper, et al.. (2019). Functional Connectivities Are More Informative Than Anatomical Variables in Diagnostic Classification of Autism. Brain Connectivity. 9(8). 604–612. 20 indexed citations
9.
Kinnear, Mikaela, et al.. (2018). Local Cortical Gyrification is Increased in Children With Autism Spectrum Disorders, but Decreases Rapidly in Adolescents. Cerebral Cortex. 29(6). 2412–2423. 40 indexed citations
10.
Datko, Michael, Jaime A. Pineda, & Ralph‐Axel Müller. (2017). Positive effects of neurofeedback on autism symptoms correlate with brain activation during imitation and observation. European Journal of Neuroscience. 47(6). 579–591. 30 indexed citations
11.
Jahedi, Afrooz, et al.. (2017). Distributed Intrinsic Functional Connectivity Patterns Predict Diagnostic Status in Large Autism Cohort. Brain Connectivity. 7(8). 515–525. 26 indexed citations
12.
13.
Falahpour, Maryam, Wesley K. Thompson, Afrooz Jahedi, et al.. (2016). Underconnected, But Not Broken? Dynamic Functional Connectivity MRI Shows Underconnectivity in Autism Is Linked to Increased Intra-Individual Variability Across Time. Brain Connectivity. 6(5). 403–414. 78 indexed citations
14.
Carper, Ruth A., et al.. (2015). Corticospinal Tract Anatomy and Functional Connectivity of Primary Motor Cortex in Autism. Journal of the American Academy of Child & Adolescent Psychiatry. 54(10). 859–867. 43 indexed citations
15.
Graham, Sarah, et al.. (2014). The Influence of Task Difficulty and Participant Age on Balance Control in ASD. Journal of Autism and Developmental Disorders. 45(5). 1419–1427. 42 indexed citations
16.
Shen, Mark D., Patricia Shih, Brandon Keehn, et al.. (2012). Atypical lexicosemantic function of extrastriate cortex in autism spectrum disorder: Evidence from functional and effective connectivity. NeuroImage. 62(3). 1780–1791. 37 indexed citations
17.
Keehn, Brandon, Alan J. Lincoln, Ralph‐Axel Müller, & Jeanne Townsend. (2010). Attentional networks in children and adolescents with autism spectrum disorder. Journal of Child Psychology and Psychiatry. 51(11). 1251–1259. 90 indexed citations
18.
Gerckens, Ulrich, et al.. (2008). Perkutaner Nahtverschluß von Femoralarterienzugängen nach diagnostischer Herzkatheteruntersuchung oder Koronarintervention. DMW - Deutsche Medizinische Wochenschrift. 121(48). 1487–1491.
19.
Müller, Ralph‐Axel, et al.. (2004). Abnormal activity patterns in premotor cortex during sequence learning in autistic patients. Biological Psychiatry. 56(5). 323–332. 78 indexed citations
20.
Kritikos, George, Ralph‐Axel Müller, & Peter Reinartz. (1988). Optimisation for Classification of Forest Damage Classes. ESASP. 287. 303. 2 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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