Marcelo S. Caetano

730 total citations
26 papers, 356 citations indexed

About

Marcelo S. Caetano is a scholar working on Cognitive Neuroscience, Developmental and Educational Psychology and Statistics and Probability. According to data from OpenAlex, Marcelo S. Caetano has authored 26 papers receiving a total of 356 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Cognitive Neuroscience, 6 papers in Developmental and Educational Psychology and 5 papers in Statistics and Probability. Recurrent topics in Marcelo S. Caetano's work include Neural dynamics and brain function (18 papers), Neuroscience and Music Perception (14 papers) and Memory and Neural Mechanisms (7 papers). Marcelo S. Caetano is often cited by papers focused on Neural dynamics and brain function (18 papers), Neuroscience and Music Perception (14 papers) and Memory and Neural Mechanisms (7 papers). Marcelo S. Caetano collaborates with scholars based in Brazil, United States and Portugal. Marcelo S. Caetano's co-authors include Mark Laubach, Nandakumar S. Narayanan, K L Parker, Nicole K. Horst, Russell M. Church, Linda M. Amarante, Nathaniel J. Smith, Amy F.T. Arnsten, André M. Cravo and Lu E. Jin and has published in prestigious journals such as Journal of Neuroscience, SHILAP Revista de lepidopterología and NeuroImage.

In The Last Decade

Marcelo S. Caetano

23 papers receiving 346 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Marcelo S. Caetano Brazil	9	277	119	36	35	31	26	356
Elijah A. Petter United States	9	292 1.1×	135 1.1×	32 0.9×	40 1.1×	36 1.2×	12	391
Nicholas A. Lusk United States	7	276 1.0×	103 0.9×	28 0.8×	27 0.8×	42 1.4×	12	362
M. Gabriela Costello United States	10	372 1.3×	91 0.8×	33 0.9×	26 0.7×	35 1.1×	12	438
Masashi Koizumi Japan	8	458 1.7×	135 1.1×	29 0.8×	16 0.5×	39 1.3×	11	526
Freya E. Cooper United Kingdom	8	253 0.9×	53 0.4×	54 1.5×	27 0.8×	30 1.0×	8	336
G. Bezzina United Kingdom	13	220 0.8×	171 1.4×	24 0.7×	18 0.5×	36 1.2×	16	331
L.E. Ribeiro-do-Valle Brazil	8	152 0.5×	112 0.9×	25 0.7×	17 0.5×	57 1.8×	22	289
Rebecca Stevenson United States	7	235 0.8×	105 0.9×	33 0.9×	23 0.7×	40 1.3×	8	376
Dan Lopez‐Paniagua United States	6	280 1.0×	115 1.0×	31 0.9×	50 1.4×	21 0.7×	7	357
Kristóf Giber Hungary	4	249 0.9×	109 0.9×	36 1.0×	35 1.0×	19 0.6×	4	328

Countries citing papers authored by Marcelo S. Caetano

Since Specialization

Citations

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

Fields of papers citing papers by Marcelo S. Caetano

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Marcelo S. Caetano. 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 Marcelo S. Caetano. The network helps show where Marcelo S. Caetano may publish in the future.

Co-authorship network of co-authors of Marcelo S. Caetano

This figure shows the co-authorship network connecting the top 25 collaborators of Marcelo S. Caetano. A scholar is included among the top collaborators of Marcelo S. Caetano 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 Marcelo S. Caetano. Marcelo S. Caetano 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

Ferreira, Tatiana Lima, et al.. (2024). Insular and prelimbic cortices control behavioral accuracy and precision in a temporal decision-making task in rats. Behavioural Brain Research. 465. 114961–114961.

Domeniconi, Camila, et al.. (2023). Análise da Viabilidade de Uso do FNIRS em Atividades Educacionais com Crianças e Jovens com Deficiência Intelectual e Autismo. SHILAP Revista de lepidopterología. 29.

Oliveira, Eliezyer Fermino de, et al.. (2022). Time encoding migrates from prefrontal cortex to dorsal striatum during learning of a self-timed response duration task. eLife. 11. 3 indexed citations

Rose, Júlio C. de, et al.. (2021). Equivalence relations do exist before they are tested: Confirmatory evidence revealed by EEG measurements. Journal of the Experimental Analysis of Behavior. 115(1). 284–295. 2 indexed citations

Machado, Armando, et al.. (2020). Rules of Conduct for Behavior Analysts in the Presence of Hypothetical Constructs: A Commentary on Eckard and Lattal (2020). Perspectives on Behavior Science. 43(4). 791–802. 3 indexed citations

Laubach, Mark, Linda M. Amarante, Marcelo S. Caetano, & Nicole K. Horst. (2020). Reward signaling by the rodent medial frontal cortex. International review of neurobiology. 158. 115–133. 4 indexed citations

Biazoli, Claudinei Eduardo, et al.. (2020). Differences in perceived durations between plausible biological and non-biological stimuli. Experimental Brain Research. 239(1). 161–173.

Cravo, André M., et al.. (2019). Rats can learn a temporal task in a single session. Behavioural Processes. 170. 103986–103986. 5 indexed citations

Caetano, Marcelo S., et al.. (2019). A model for the peak-interval task based on neural oscillation-delimited states. Behavioural Processes. 168. 103941–103941. 1 indexed citations

10.

Cravo, André M., et al.. (2019). Temporal regularity and stimulus control in multiple fixed interval schedules. Behavioural Processes. 171. 104019–104019. 1 indexed citations

11.

Sato, João Ricardo, et al.. (2018). A common representation of time across visual and auditory modalities. Neuropsychologia. 119. 223–232. 11 indexed citations

12.

Caetano, Marcelo S., et al.. (2017). Individual differences in long-range time representation. Attention Perception & Psychophysics. 79(3). 833–840. 7 indexed citations

13.

Amarante, Linda M., Marcelo S. Caetano, & Mark Laubach. (2017). Medial Frontal Theta Is Entrained to Rewarded Actions. Journal of Neuroscience. 37(44). 10757–10769. 29 indexed citations

14.

Laubach, Mark, Marcelo S. Caetano, & Nandakumar S. Narayanan. (2015). Mistakes were made: Neural mechanisms for the adaptive control of action initiation by the medial prefrontal cortex. Journal of Physiology-Paris. 109(1-3). 104–117. 59 indexed citations

15.

Parker, K L, et al.. (2013). Executive dysfunction in Parkinson’s disease and timing deficits. Frontiers in Integrative Neuroscience. 7. 75–75. 80 indexed citations

16.

Caetano, Marcelo S., et al.. (2012). Lost in Transition: Aging-Related Changes in Executive Control by the Medial Prefrontal Cortex. Journal of Neuroscience. 32(11). 3765–3777. 27 indexed citations

17.

Caetano, Marcelo S., et al.. (2012). Stimulus control in multiple temporal discriminations. Learning & Behavior. 40(4). 520–529. 7 indexed citations

18.

Smith, Nathaniel J., et al.. (2010). Reversible Inactivation of Rat Premotor Cortex Impairs Temporal Preparation, but not Inhibitory Control, During Simple Reaction-Time Performance. Frontiers in Integrative Neuroscience. 4. 124–124. 45 indexed citations

19.

Caetano, Marcelo S., et al.. (2010). The effect of stimulus discriminability on strategies for learning multiple temporal discriminations. Behavioural Processes. 84(1). 476–483. 6 indexed citations

20.

Caetano, Marcelo S. & Russell M. Church. (2009). A comparison of responses and stimuli as time markers. Behavioural Processes. 81(2). 298–302. 8 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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