Andrew Morgan

993 total citations
20 papers, 507 citations indexed

About

Andrew Morgan is a scholar working on Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging and Computational Mechanics. According to data from OpenAlex, Andrew Morgan has authored 20 papers receiving a total of 507 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Cognitive Neuroscience, 9 papers in Radiology, Nuclear Medicine and Imaging and 2 papers in Computational Mechanics. Recurrent topics in Andrew Morgan's work include Advanced MRI Techniques and Applications (9 papers), Functional Brain Connectivity Studies (8 papers) and Visual perception and processing mechanisms (7 papers). Andrew Morgan is often cited by papers focused on Advanced MRI Techniques and Applications (9 papers), Functional Brain Connectivity Studies (8 papers) and Visual perception and processing mechanisms (7 papers). Andrew Morgan collaborates with scholars based in United States, United Kingdom and Netherlands. Andrew Morgan's co-authors include M. Mandelkern, Edythe D. London, Dara G. Ghahremani, Chelsea L. Robertson, Golnaz Tabibnia, Buyean Lee, Adam R. Aron, Russell A. Poldrack, Amira K. Brown and John Monterosso and has published in prestigious journals such as Nature Communications, Journal of Neuroscience and NeuroImage.

In The Last Decade

Andrew Morgan

19 papers receiving 498 citations

Peers

Andrew Morgan

CMN

RNMI

PMH

NEURO

Siân E. Robson United Kingdom

Hang-Keun Kim South Korea

Shi‐Jiang Li United States

Youngsun Cho United States

Xun Zhu United States

Jorge Arrubla Germany

V.S. Mattay United States

Neva M. Corrigan United States

Darren Price United Kingdom

Ryu Kurimoto Japan

Siân E. Robson United Kingdom

Andrew Morgan

600 ×2.0

122 ×0.9

CMN

195 ×1.7

RNMI

64 ×1.0

PMH

29 ×0.6

NEURO

Citations per year, relative to Andrew Morgan Andrew Morgan (= 1×) peers Siân E. Robson

Countries citing papers authored by Andrew Morgan

Since Specialization

Citations

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

Fields of papers citing papers by Andrew Morgan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Andrew Morgan. 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 Andrew Morgan. The network helps show where Andrew Morgan may publish in the future.

Co-authorship network of co-authors of Andrew Morgan

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

All Works

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20 of 20 papers shown

Stirnberg, Rüdiger, et al.. (2025). T1234 : A distortion‐matched structural scan solution to misregistration of high resolution fMRI data. Magnetic Resonance in Medicine. 94(2). 713–723. 1 indexed citations

Huber, Laurentius, Rüdiger Stirnberg, Andrew Morgan, et al.. (2025). Short‐term gradient imperfections in high‐resolution EPI lead to Fuzzy Ripple artifacts. Magnetic Resonance in Medicine. 94(2). 571–587. 1 indexed citations

Huber, Laurentius, Michael Köehler, Rüdiger Stirnberg, et al.. (2025). Advanced Echo-planar Parallel Imaging with Gradient Harmonization (AEPIG): an optimization strategy for fast high resolution fMRI. Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition.

Kronemer, Sharif I., et al.. (2024). Visual imagery vividness correlates with afterimage conscious perception. Neuroscience of Consciousness. 2024(1). niae032–niae032. 1 indexed citations

Bergmann, Johanna, et al.. (2024). Cortical depth profiles in primary visual cortex for illusory and imaginary experiences. Nature Communications. 15(1). 1002–1002. 12 indexed citations

Chai, Yuhui, Andrew Morgan, Linqing Li, et al.. (2024). Unlocking near-whole-brain, layer-specific functional connectivity with 3D VAPER fMRI. Imaging Neuroscience. 2. 5 indexed citations

Chai, Yuhui, Andrew Morgan, Daniel A. Handwerker, et al.. (2024). Improving laminar fMRI specificity by reducing macrovascular bias revealed by respiration effects. Imaging Neuroscience. 2. 5 indexed citations

Papale, Paolo, Feng Wang, Andrew Morgan, et al.. (2023). The representation of occluded image regions in area V1 of monkeys and humans. Current Biology. 33(18). 3865–3871.e3. 11 indexed citations

Huber, Laurentius, Benedikt A. Poser, Peter A. Bandettini, et al.. (2021). LayNii: A software suite for layer-fMRI. NeuroImage. 237. 118091–118091. 73 indexed citations

10.

Svanera, Michele, Andrew Morgan, Lucy S. Petro, & Lars Muckli. (2021). A self-supervised deep neural network for image completion resembles early visual cortex fMRI activity patterns for occluded scenes. Journal of Vision. 21(7). 5–5. 1 indexed citations

11.

Rua, Catarina, William T. Clarke, Ian D. Driver, et al.. (2020). Multi-centre, multi-vendor reproducibility of 7T QSM and R2* in the human brain: Results from the UK7T study. NeuroImage. 223. 117358–117358. 24 indexed citations

12.

Morgan, Nathaniel, Svetlana Tokareva, Xiaodong Liu, & Andrew Morgan. (2020). A machine learning approach for detecting shocks with high-order hydrodynamic methods. AIAA Scitech 2020 Forum. 14 indexed citations

13.

Clarke, William T., Olivier Mougin, Ian D. Driver, et al.. (2019). Multi-site harmonization of 7 tesla MRI neuroimaging protocols. NeuroImage. 206. 116335–116335. 27 indexed citations

14.

Morgan, Andrew, Lucy S. Petro, & Lars Muckli. (2019). Scene Representations Conveyed by Cortical Feedback to Early Visual Cortex Can Be Described by Line Drawings. Journal of Neuroscience. 39(47). 9410–9423. 19 indexed citations

15.

Morgan, Andrew, Lucy S. Petro, & Lars Muckli. (2018). Cortical feedback to superficial layers of V1 contains predictive scene information.. 1 indexed citations

16.

Kohno, Milky, Dara G. Ghahremani, Angelica M. Morales, et al.. (2013). Risk-Taking Behavior: Dopamine D2/D3 Receptors, Feedback, and Frontolimbic Activity. Cerebral Cortex. 25(1). 236–245. 83 indexed citations

17.

Ishibashi, Kenji, Chelsea L. Robertson, M. Mandelkern, Andrew Morgan, & Edythe D. London. (2013). The Simplified Reference Tissue Model with ¹⁸F-Fallypride Positron Emission Tomography: Choice of Reference Region. Molecular Imaging. 12(8). 18 indexed citations

18.

Ghahremani, Dara G., Buyean Lee, Chelsea L. Robertson, et al.. (2012). Striatal Dopamine D₂/D₃Receptors Mediate Response Inhibition and Related Activity in Frontostriatal Neural Circuitry in Humans. Journal of Neuroscience. 32(21). 7316–7324. 189 indexed citations

19.

Burns, Joseph W., et al.. (2008). Parametric reconstruction of internal building structures via canonical scattering mechanisms. Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing. 16 indexed citations

20.

Pratt, Jay, et al.. (2000). The role of the fixation location in inhibition of return.. Canadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale. 54(3). 186–195. 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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