Alexander Provost

1.0k total citations
25 papers, 775 citations indexed

About

Alexander Provost is a scholar working on Cognitive Neuroscience, Signal Processing and Experimental and Cognitive Psychology. According to data from OpenAlex, Alexander Provost has authored 25 papers receiving a total of 775 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Cognitive Neuroscience, 8 papers in Signal Processing and 5 papers in Experimental and Cognitive Psychology. Recurrent topics in Alexander Provost's work include Neuroscience and Music Perception (13 papers), Hearing Loss and Rehabilitation (9 papers) and Neural and Behavioral Psychology Studies (9 papers). Alexander Provost is often cited by papers focused on Neuroscience and Music Perception (13 papers), Hearing Loss and Rehabilitation (9 papers) and Neural and Behavioral Psychology Studies (9 papers). Alexander Provost collaborates with scholars based in Australia, Hungary and United States. Alexander Provost's co-authors include Andrew Heathcote, Janette L. Smith, Juanita Todd, Frini Karayanidis, Scott Brown, Sharna D. Jamadar, Patricia T. Michie, Elizabeth A. Smith, István Winkler and Gavin Cooper and has published in prestigious journals such as Psychological Review, Journal of Neurophysiology and Neuroscience.

In The Last Decade

Alexander Provost

25 papers receiving 764 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Alexander Provost Australia 17 689 225 63 54 49 25 775
Matthew S. Tata Canada 13 450 0.7× 140 0.6× 35 0.6× 43 0.8× 25 0.5× 36 566
Nicole Wetzel Germany 19 886 1.3× 376 1.7× 18 0.3× 60 1.1× 115 2.3× 42 1.0k
Cameron D. Hassall Canada 13 492 0.7× 108 0.5× 8 0.1× 31 0.6× 28 0.6× 37 635
Ferenc Honbolygó Hungary 14 426 0.6× 235 1.0× 16 0.3× 25 0.5× 239 4.9× 57 573
Veronica Mazza Italy 18 1.0k 1.5× 274 1.2× 7 0.1× 40 0.7× 87 1.8× 56 1.2k
David Sutterer United States 13 978 1.4× 224 1.0× 9 0.1× 30 0.6× 119 2.4× 20 1.1k
Silu Fan China 15 988 1.4× 198 0.9× 19 0.3× 21 0.4× 56 1.1× 24 1.0k
Clémence Roger France 9 611 0.9× 96 0.4× 28 0.4× 41 0.8× 41 0.8× 20 699
Kamila Śmigasiewicz Germany 18 882 1.3× 120 0.5× 5 0.1× 61 1.1× 79 1.6× 41 968
Jaclyn L. Farrens United States 5 432 0.6× 230 1.0× 18 0.3× 39 0.7× 32 0.7× 5 550

Countries citing papers authored by Alexander Provost

Since Specialization
Citations

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

Fields of papers citing papers by Alexander Provost

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alexander Provost

This figure shows the co-authorship network connecting the top 25 collaborators of Alexander Provost. A scholar is included among the top collaborators of Alexander Provost 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 Alexander Provost. Alexander Provost 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.
Auksztulewicz, Ryszard, et al.. (2021). Hierarchical Learning of Statistical Regularities over Multiple Timescales of Sound Sequence Processing: A Dynamic Causal Modeling Study. Journal of Cognitive Neuroscience. 33(8). 1–14. 8 indexed citations
2.
Todd, Juanita, et al.. (2021). A cognitive model of response omissions in distraction paradigms. Memory & Cognition. 50(5). 962–978. 6 indexed citations
3.
Todd, Juanita, et al.. (2018). Initial Uncertainty Impacts Statistical Learning in Sound Sequence Processing. Neuroscience. 389. 41–53. 6 indexed citations
4.
Todd, Juanita, et al.. (2017). Time as context: The influence of hierarchical patterning on sensory inference. Schizophrenia Research. 191. 123–131. 19 indexed citations
5.
Todd, Juanita, et al.. (2016). Initial uncertainty impacts statistical learning in sound sequence processing. Journal of Physiology-Paris. 110(4). 497–507. 7 indexed citations
6.
Winkler, István, et al.. (2016). Biased relevance filtering in the auditory system: A test of confidence-weighted first-impressions. Biological Psychology. 115. 101–111. 16 indexed citations
7.
Provost, Alexander & Andrew Heathcote. (2015). Titrating decision processes in the mental rotation task.. Psychological Review. 122(4). 735–754. 20 indexed citations
8.
Winkler, István, et al.. (2015). Surprising sequential effects on MMN. Biological Psychology. 116. 47–56. 26 indexed citations
9.
Karayanidis, Frini, W. Ross Fulham, Alexander Provost, et al.. (2014). Reactive control processes contributing to residual switch cost and mixing cost across the adult lifespan. Frontiers in Psychology. 5. 383–383. 24 indexed citations
10.
Provost, Alexander, et al.. (2014). Altering the primacy bias—How does a prior task affect mismatch negativity?. Psychophysiology. 51(5). 437–445. 25 indexed citations
11.
Todd, Juanita, et al.. (2014). Mismatch negativity (MMN) to pitch change is susceptible to order-dependent bias. Frontiers in Neuroscience. 8. 180–180. 30 indexed citations
12.
Todd, Juanita, et al.. (2013). What controls gain in gain control? Mismatch negativity (MMN), priors and system biases. Brain Topography. 27(4). 578–589. 33 indexed citations
13.
Provost, Alexander, Blake W. Johnson, Frini Karayanidis, Scott Brown, & Andrew Heathcote. (2013). Two Routes to Expertise in Mental Rotation. Cognitive Science. 37(7). 1321–1342. 27 indexed citations
14.
Smith, Janette L., Sharna D. Jamadar, Alexander Provost, & Patricia T. Michie. (2012). Motor and non-motor inhibition in the Go/NoGo task: An ERP and fMRI study. International Journal of Psychophysiology. 87(3). 244–253. 98 indexed citations
15.
Todd, Juanita, et al.. (2012). Not so primitive: context-sensitive meta-learning about unattended sound sequences. Journal of Neurophysiology. 109(1). 99–105. 35 indexed citations
16.
Todd, Juanita, Alexander Provost, & Gavin Cooper. (2011). Lasting first impressions: A conservative bias in automatic filters of the acoustic environment. Neuropsychologia. 49(12). 3399–3405. 47 indexed citations
17.
Karayanidis, Frini, Alexander Provost, Scott Brown, Bryan Paton, & Andrew Heathcote. (2010). Switch‐specific and general preparation map onto different ERP components in a task‐switching paradigm. Psychophysiology. 48(4). 559–568. 72 indexed citations
18.
Levi, Dennis M., David Whitaker, & Alexander Provost. (2009). Amblyopia masks the scale invariance of normal central vision. Journal of Vision. 9(1). 22–22. 5 indexed citations
19.
Karayanidis, Frini, et al.. (2009). Anticipatory reconfiguration elicited by fully and partially informative cues that validly predict a switch in task. Cognitive Affective & Behavioral Neuroscience. 9(2). 202–215. 103 indexed citations
20.
Smith, Janette L., Elizabeth A. Smith, Alexander Provost, & Andrew Heathcote. (2009). Sequence effects support the conflict theory of N2 and P3 in the Go/NoGo task. International Journal of Psychophysiology. 75(3). 217–226. 92 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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