Matthew Piva

561 total citations
12 papers, 375 citations indexed

About

Matthew Piva is a scholar working on Social Psychology, Cognitive Neuroscience and Molecular Biology. According to data from OpenAlex, Matthew Piva has authored 12 papers receiving a total of 375 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Social Psychology, 4 papers in Cognitive Neuroscience and 3 papers in Molecular Biology. Recurrent topics in Matthew Piva's work include Neuroendocrine regulation and behavior (5 papers), Attachment and Relationship Dynamics (3 papers) and Evolutionary Psychology and Human Behavior (3 papers). Matthew Piva is often cited by papers focused on Neuroendocrine regulation and behavior (5 papers), Attachment and Relationship Dynamics (3 papers) and Evolutionary Psychology and Human Behavior (3 papers). Matthew Piva collaborates with scholars based in United States, Canada and Russia. Matthew Piva's co-authors include Steve W. C. Chang, Olga Dal Monte, Xian Zhang, Joy Hirsch, J. Adam Noah, Craig D. C. Bailey, Amrita R. Nair, Ifat Levy, Evelyn K. Lambe and Kevin Anderson and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Trends in Cognitive Sciences and Journal of Neurophysiology.

In The Last Decade

Matthew Piva

12 papers receiving 371 citations

Peers

Matthew Piva

CN

SP

ECP

MB

CMN

Tulio Guadalupe Netherlands

Débora da Paz Maciel Kimura Canada

Kevin M. Tan United States

Janina Eberhart United Kingdom

Kara I. Gabriel United States

Lingfei Tang United States

Marco Nigro Italy

Emily Dunn United States

Koji Toda Japan

Chieko Kato Japan

Tulio Guadalupe Netherlands

Matthew Piva

249 ×1.4

CN

109 ×0.7

SP

80 ×1.2

ECP

63 ×1.2

MB

21 ×0.5

CMN

Citations per year, relative to Matthew Piva Matthew Piva (= 1×) peers Tulio Guadalupe

Countries citing papers authored by Matthew Piva

Since Specialization

Citations

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

Fields of papers citing papers by Matthew Piva

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthew Piva

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

All Works

Sort: Min cites: Since: Top N: Style:

12 of 12 papers shown

1.

Piva, Matthew, et al.. (2019). Combinatorial Oxytocin Neuropharmacology in Social Cognition. Trends in Cognitive Sciences. 24(1). 8–12. 11 indexed citations

2.

Piva, Matthew, et al.. (2019). The dorsomedial prefrontal cortex computes task-invariant relative subjective value for self and other. eLife. 8. 47 indexed citations

3.

Piva, Matthew & Steve W. C. Chang. (2018). An integrated framework for the role of oxytocin in multistage social decision‐making. American Journal of Primatology. 80(10). e22735–e22735. 29 indexed citations

4.

Piva, Matthew, et al.. (2017). Ca2+ signaling machinery is present at intercellular junctions and structures associated with junction turnover in rat Sertoli cells†. Biology of Reproduction. 96(6). 1288–1302. 23 indexed citations

5.

Piva, Matthew, Xian Zhang, J. Adam Noah, Steve W. C. Chang, & Joy Hirsch. (2017). Distributed Neural Activity Patterns during Human-to-Human Competition. Frontiers in Human Neuroscience. 11. 571–571. 43 indexed citations

6.

Piva, Matthew, et al.. (2017). Social learning through prediction error in the brain. npj Science of Learning. 2(1). 8–8. 88 indexed citations

7.

Vogl, A. Wayne, et al.. (2017). The endoplasmic reticulum, calcium signaling and junction turnover in Sertoli cells. Reproduction. 155(2). R93–R104. 15 indexed citations

8.

Monte, Olga Dal, et al.. (2017). Oxytocin under opioid antagonism leads to supralinear enhancement of social attention. Proceedings of the National Academy of Sciences. 114(20). 5247–5252. 41 indexed citations

9.

Monte, Olga Dal, et al.. (2016). Live interaction distinctively shapes social gaze dynamics in rhesus macaques. Journal of Neurophysiology. 116(4). 1626–1643. 19 indexed citations

10.

Piva, Matthew, et al.. (2013). Nicotinic acetylcholine receptors in attention circuitry: the role of layer VI neurons of prefrontal cortex. Cellular and Molecular Life Sciences. 71(7). 1225–1244. 39 indexed citations

11.

Wang, Wenyan, et al.. (2012). Transmembrane semaphorin5B is proteolytically processed into a repulsive neural guidance cue. Journal of Neurochemistry. 123(1). 135–146. 18 indexed citations

12.

David, Renaud, et al.. (2008). Evaluation of apathy using reaction time task in neurodegenerative diseases. European Psychiatry. 23. S193–S193. 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.

Explore authors with similar magnitude of impact