Sara Matias

1.6k total citations
11 papers, 796 citations indexed

About

Sara Matias is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Molecular Biology. According to data from OpenAlex, Sara Matias has authored 11 papers receiving a total of 796 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Cognitive Neuroscience, 6 papers in Cellular and Molecular Neuroscience and 1 paper in Molecular Biology. Recurrent topics in Sara Matias's work include Neural dynamics and brain function (7 papers), Photoreceptor and optogenetics research (3 papers) and EEG and Brain-Computer Interfaces (3 papers). Sara Matias is often cited by papers focused on Neural dynamics and brain function (7 papers), Photoreceptor and optogenetics research (3 papers) and EEG and Brain-Computer Interfaces (3 papers). Sara Matias collaborates with scholars based in Portugal, United States and France. Sara Matias's co-authors include Zachary F. Mainen, Guillaume P. Dugué, Eran Lottem, Patricia Correia, Rui M. Costa, Fatuel Tecuapetla, Elena Dreosti, Gonçalo Lopes, Adam R. Kampff and Niccolò Bonacchi and has published in prestigious journals such as Nature, Nature Communications and Neuron.

In The Last Decade

Sara Matias

11 papers receiving 792 citations

Peers

Sara Matias

CMN

CN

MB

SP

NEURO

Shay Q. Neufeld United States

Sofia Soares Portugal

Kathleen A. Martin United States

Justin L. Shobe United States

Antonia Marín‐Burgin Argentina

Arseny Finkelstein Israel

Patricia Correia France

Sue Ann Koay United States

Fuyuki Karube Japan

Corey B. Puryear United States

Shay Q. Neufeld United States

Sara Matias

489 ×1.1

CMN

436 ×1.1

CN

171 ×1.1

MB

87 ×0.9

SP

59 ×0.9

NEURO

Citations per year, relative to Sara Matias Sara Matias (= 1×) peers Shay Q. Neufeld

Countries citing papers authored by Sara Matias

Since Specialization

Citations

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

Fields of papers citing papers by Sara Matias

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sara Matias

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

All Works

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11 of 11 papers shown

1.

Hennig, Jay A., et al.. (2025). Prospective contingency explains behavior and dopamine signals during associative learning. Nature Neuroscience. 28(6). 1280–1292. 2 indexed citations

2.

Qiao, Zheng, et al.. (2025). An opponent striatal circuit for distributional reinforcement learning. Nature. 639(8055). 717–726. 3 indexed citations

3.

Matias, Sara, Hao Wu, Simona Temereanca, et al.. (2025). Interpretable deep learning for deconvolutional analysis of neural signals. Neuron. 113(8). 1151–1168.e13. 2 indexed citations

4.

Amo, Ryunosuke, Sara Matias, Akihiro Yamanaka, et al.. (2022). A gradual temporal shift of dopamine responses mirrors the progression of temporal difference error in machine learning. Nature Neuroscience. 25(8). 1082–1092. 44 indexed citations

5.

Qiao, Zheng, et al.. (2020). Distributional Reinforcement Learning in the Brain. Trends in Neurosciences. 43(12). 980–997. 40 indexed citations

6.

Matias, Sara, Eran Lottem, Guillaume P. Dugué, & Zachary F. Mainen. (2017). Activity patterns of serotonin neurons underlying cognitive flexibility. eLife. 6. 148 indexed citations

7.

Correia, Patricia, Sara Matias, & Zachary F. Mainen. (2017). Stereotaxic Adeno-associated Virus Injection and Cannula Implantation in the Dorsal Raphe Nucleus of Mice. BIO-PROTOCOL. 7(18). e2549–e2549. 14 indexed citations

8.

Lopes, Gonçalo, Niccolò Bonacchi, Joana P. Neto, et al.. (2015). Bonsai: an event-based framework for processing and controlling data streams. Frontiers in Neuroinformatics. 9. 7–7. 319 indexed citations

9.

Tecuapetla, Fatuel, Sara Matias, Guillaume P. Dugué, Zachary F. Mainen, & Rui M. Costa. (2014). Balanced activity in basal ganglia projection pathways is critical for contraversive movements. Nature Communications. 5(1). 4315–4315. 144 indexed citations

10.

Dugué, Guillaume P., Magor L. Lörincz, Eran Lottem, et al.. (2014). Optogenetic Recruitment of Dorsal Raphe Serotonergic Neurons Acutely Decreases Mechanosensory Responsivity in Behaving Mice. PLoS ONE. 9(8). e105941–e105941. 44 indexed citations

11.

Figueira, José Rui, et al.. (2011). Electre Tri-C, a multiple criteria decision aiding sorting model applied to assisted reproduction. International Journal of Medical Informatics. 80(4). 262–273. 36 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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