Sarah M. Haigh

1.5k total citations
54 papers, 1.0k citations indexed

About

Sarah M. Haigh is a scholar working on Cognitive Neuroscience, Psychiatry and Mental health and Experimental and Cognitive Psychology. According to data from OpenAlex, Sarah M. Haigh has authored 54 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Cognitive Neuroscience, 10 papers in Psychiatry and Mental health and 9 papers in Experimental and Cognitive Psychology. Recurrent topics in Sarah M. Haigh's work include Neuroscience and Music Perception (17 papers), Neural dynamics and brain function (14 papers) and Visual perception and processing mechanisms (12 papers). Sarah M. Haigh is often cited by papers focused on Neuroscience and Music Perception (17 papers), Neural dynamics and brain function (14 papers) and Visual perception and processing mechanisms (12 papers). Sarah M. Haigh collaborates with scholars based in United States, United Kingdom and Israel. Sarah M. Haigh's co-authors include Dean F. Salisbury, Brian A. Coffman, Arnold J. Wilkins, Nancy J. Minshew, Marlene Behrmann, Shaun M. Eack, David J. Heeger, Ilan Dinstein, Nicholas R. Cooper and Carla A. Mazefsky and has published in prestigious journals such as NeuroImage, Biological Psychiatry and Neuropsychologia.

In The Last Decade

Sarah M. Haigh

50 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sarah M. Haigh United States 20 829 249 109 104 98 54 1.0k
Henrietta Mustovic Switzerland 6 537 0.6× 150 0.6× 207 1.9× 237 2.3× 38 0.4× 6 938
Roozbeh Rezaie United States 21 1.0k 1.2× 209 0.8× 123 1.1× 186 1.8× 43 0.4× 45 1.4k
Martin D. Vestergaard United Kingdom 19 810 1.0× 146 0.6× 253 2.3× 46 0.4× 94 1.0× 35 1.1k
Nicole Bruneau France 20 1.1k 1.4× 176 0.7× 209 1.9× 63 0.6× 153 1.6× 30 1.3k
Takayuki Nakahachi Japan 19 678 0.8× 272 1.1× 76 0.7× 57 0.5× 26 0.3× 35 968
Katharina Pauly Germany 17 592 0.7× 333 1.3× 300 2.8× 155 1.5× 57 0.6× 25 943
Takefumi Ueno Japan 19 601 0.7× 183 0.7× 103 0.9× 81 0.8× 21 0.2× 54 974
Aurélie Bidet‐Caulet France 18 933 1.1× 103 0.4× 361 3.3× 101 1.0× 123 1.3× 39 1.1k
Kristiina Kompus Norway 22 1.1k 1.3× 579 2.3× 316 2.9× 93 0.9× 44 0.4× 47 1.6k
Yang‐Teng Fan Taiwan 15 658 0.8× 207 0.8× 82 0.8× 168 1.6× 19 0.2× 41 932

Countries citing papers authored by Sarah M. Haigh

Since Specialization
Citations

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

Fields of papers citing papers by Sarah M. Haigh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sarah M. Haigh

This figure shows the co-authorship network connecting the top 25 collaborators of Sarah M. Haigh. A scholar is included among the top collaborators of Sarah M. Haigh 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 Sarah M. Haigh. Sarah M. Haigh 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.
Haigh, Sarah M., et al.. (2025). Identifying overlapping and distinctive traits of autism and schizophrenia using machine learning classification. Cognitive Neuropsychiatry. 30(2). 69–91.
2.
Fernandez, Ritin, et al.. (2025). Falls in an Australian Hospital During the COVID-19 Pandemic: A Study of Patient Safety Incident Reports. Journal of Patient Safety. 21(4). 220–225.
3.
Berryhill, Marian E., et al.. (2024). Pattern glare sensitivity distinguishes subclinical autism and schizotypy. Cognitive Neuropsychiatry. 29(3). 155–172. 3 indexed citations
4.
Penacchio, Olivier, Xavier Otazu, Arnold J. Wilkins, & Sarah M. Haigh. (2023). A mechanistic account of visual discomfort. Frontiers in Neuroscience. 17. 1200661–1200661. 17 indexed citations
5.
Haigh, Sarah M., et al.. (2023). Auditory discomfort in visually sensitive individuals. Frontiers in Psychology. 14. 1126481–1126481. 1 indexed citations
6.
Haigh, Sarah M., et al.. (2023). Working memory and sensory memory in subclinical high schizotypy: An avenue for understanding schizophrenia?. European Journal of Neuroscience. 57(9). 1577–1596. 4 indexed citations
7.
Haigh, Sarah M., et al.. (2022). People with high schizotypy experience more illusions in the Pattern Glare Test: Consistent with the hyperexcitability hypothesis. European Journal of Neuroscience. 57(2). 388–399. 4 indexed citations
8.
Haigh, Sarah M., et al.. (2021). Abnormalities in cortical pattern of coherence in migraine detected using ultra high-density EEG. Brain Communications. 3(2). fcab061–fcab061. 19 indexed citations
9.
Salisbury, Dean F., Brian A. Coffman, & Sarah M. Haigh. (2020). Reductions in Complex Mismatch Negativity to Extra Tone Gestalt Pattern Deviance in First-Episode Schizophrenia. Frontiers in Psychiatry. 11. 505–505. 9 indexed citations
10.
Haigh, Sarah M., et al.. (2018). Processing Speed is Impaired in Adults with Autism Spectrum Disorder, and Relates to Social Communication Abilities. Journal of Autism and Developmental Disorders. 48(8). 2653–2662. 67 indexed citations
11.
Coffman, Brian A., et al.. (2017). Impairment in Mismatch Negativity but not Repetition Suppression in Schizophrenia. Brain Topography. 30(4). 521–530. 23 indexed citations
12.
Salisbury, Dean F., et al.. (2017). Complex mismatch negativity to tone pair deviants in long-term schizophrenia and in the first-episode schizophrenia spectrum. Schizophrenia Research. 191. 18–24. 24 indexed citations
13.
Coffman, Brian A., et al.. (2017). 193. Emitted P3a and P3b in Chronic Schizophrenia and in First-Episode Schizophrenia-Spectrum Psychosis. Biological Psychiatry. 81(10). S80–S80.
14.
Haigh, Sarah M., David J. Heeger, Laurie M. Heller, et al.. (2016). No difference in cross-modal attention or sensory discrimination thresholds in autism and matched controls. Vision Research. 121. 85–94. 12 indexed citations
15.
Haigh, Sarah M., Scott Barb, Nancy J. Minshew, et al.. (2016). Differential sensory fMRI signatures in autism and schizophrenia: Analysis of amplitude and trial-to-trial variability. Schizophrenia Research. 175(1-3). 12–19. 28 indexed citations
16.
Coffman, Brian A., et al.. (2016). Event-related potentials demonstrate deficits in acoustic segmentation in schizophrenia. Schizophrenia Research. 173(1-2). 109–115. 12 indexed citations
17.
Haigh, Sarah M., David J. Heeger, Ilan Dinstein, Nancy J. Minshew, & Marlene Behrmann. (2014). Cortical Variability in the Sensory-Evoked Response in Autism. Journal of Autism and Developmental Disorders. 45(5). 1176–1190. 84 indexed citations
18.
Haigh, Sarah M., Wolfgang Jaschinski, Peter M. Allen, & Arnold J. Wilkins. (2013). Accommodation to Uncomfortable Patterns. Perception. 42(2). 208–222. 7 indexed citations
19.
Haigh, Sarah M., et al.. (2013). Discomfort and the cortical haemodynamic response to coloured gratings. Vision Research. 89. 47–53. 58 indexed citations
20.
Edwards, Adrian, Reina Evans-Paulson, Joanna Dundon, et al.. (2006). Personalised risk communication for informed decision making about taking screening tests (Review). 53 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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