Summary: A new paper identifies 100 of the most cited neuroscience research papers. Of these papers, 78 focus on five topics. According to the authors of the paper, the most cited neuroscience research topics include the prefrontal cortex, neural connectivity, methodology, brain mapping and neurological disorders. The findings could have significant impact for future neuroscience studies.

Source: Frontiers.

A study has identified the 100 most-cited neuroscience papers, and their research topics and journals.

A study of the 100 most-cited neuroscience articles has revealed that 78 of these papers cover five topics, including neurological disorders, the prefrontal cortex, brain connectivity, brain mapping and methodology studies. The study allows scientists, policy-makers and investors to quickly identify the most-cited articles and impactful research in neuroscience.

Neuroscience research aims to understand neural structure and function, and how this relates to behavior, normal physiological processes and disease. The discipline is growing rapidly, with scientists publishing more articles each year. As researchers learn more and develop new techniques, the number of research topics grows, and it can be difficult to get a handle on the field as a whole.

“It can be difficult for newcomers to the neuroscience field or clinicians to identify the major research topics,” explains Andy Wai Kan Yeung of the University of Hong Kong, lead author on the study, which was recently published in Frontiers in Human Neuroscience. Yeung and colleagues set out to identify and analyze the 100 top-cited (referenced by other articles) papers in neuroscience.

“The aim was to provide a starting point for people conducting literature searches, so that they could quickly and easily identify the most cited work in the whole field,” says Yeung. In theory, high numbers of citations should reveal articles with a big impact in the field, and comparing citations can be an impartial and convenient way to find papers that have made a splash.

The team searched for neuroscience manuscripts on the Web of Science database, which lists citation data for articles dating to 1945. They identified and analyzed the 100 most-cited neuroscience articles and recorded information about each one, including the journals they were published in, research topic and year of publication. They also looked at the impact factor of each respective journal, which, put simply, is the average number of cites an article, in given a journal, receives per year.

The team found that the top 100 articles were published between 1972 and 2009, and the total number of cites for each article ranged from 2,138 to 7,326, with an average of 3,087. Cites were fairly evenly distributed throughout the 100 articles, meaning that no one article, or group of articles, had a disproportionately high number.

However, articles tend to attract more cites over time, with older articles having more time to be cited, while journal impact factors change over time. So, to level the playing field, the researchers also compared adjusted citation counts (the average citation count per year since the article was published) and adjusted journal impact factors (the average impact factor of the journal per year, since the article was published).

Almost half of the journals in the list have long histories, such as Nature and Science, which were established in the late 1800s. The researchers compared some of the most prestigious journals with high impact factors with the other journals on the list. “Adjusted journal impact factor did not have a significant correlation with adjusted citation count,” says Yeung. “This was surprising, as it is intuitive to think that important articles published in prestigious journals should have more citations”.

When the team grouped the papers in terms of research topic, 78 on the list covered five topics including neurological disorders, the prefrontal cortex, brain connectivity, brain mapping and methodology studies. Papers investigating brain connectivity were quite recent, indicating that this topic has recently increased in popularity and importance.

The study can help anyone interested in identifying the most important neuroscience topics. “Hopefully this study will encourage researchers to look at the identified articles and build on this impactful work,” says Yeung.

About this neuroscience research article

Funding: Funding provided by Research Grants Council of the Hong Kong Special Administrative Region, China.

Source: Melissa Cochrane – Frontiers

Image Source: NeuroscienceNews.com image is in the public domain.

Original Research: Full open access research for “At the Leading Front of Neuroscience: A Bibliometric Study of the 100 Most-Cited Articles” by Andy W. K. Yeung, Tazuko K. Goto and W. Keung Leung in Frontiers in Human Neuroscience. Published online July 21 2017 doi:10.3389/fnhum.2017.00363

Cite This NeuroscienceNews.com Article

[cbtabs][cbtab title=”MLA”]Frontiers “Study Reveals Most Impactful Neuroscience Research.” NeuroscienceNews. NeuroscienceNews, 21 July 2017.

<https://neurosciencenews.com/impactful-neuroscience-research-7145/>.[/cbtab][cbtab title=”APA”]Frontiers (2017, July 21). Study Reveals Most Impactful Neuroscience Research. NeuroscienceNew. Retrieved July 21, 2017 from https://neurosciencenews.com/impactful-neuroscience-research-7145/[/cbtab][cbtab title=”Chicago”]Frontiers “Study Reveals Most Impactful Neuroscience Research.” https://neurosciencenews.com/impactful-neuroscience-research-7145/ (accessed July 21, 2017).[/cbtab][/cbtabs]

Abstract

At the Leading Front of Neuroscience: A Bibliometric Study of the 100 Most-Cited Articles

Background: It might be difficult for clinicians and scientists to identify comprehensively the major research topics given the large number of publications. A bibliometric report that identifies the most-cited articles within the body of the relevant literature may provide insight and guidance for readers toward scientific topics that are considered important for researchers and all relevant workers of academia. To our knowledge, there is a lack of an overall evaluation of the most-cited articles and hence of a comprehensive review of major research topics in neuroscience. The present study was therefore proposed to analyze and characterize the 100 most-cited articles in neuroscience.

Methods: Based on data provided from Web of Science, the 100 most-cited articles relevant to neuroscience were identified and characterized. Information was extracted for each included article to assess for the publication year, journal published, impact factor, adjusted impact factor, citation count (total, normalized, and adjusted), reference list, authorship and article type.

Results: The total citation count for the 100 most-cited articles ranged from 7,326 to 2,138 (mean 3087.0) and the normalized citation count ranged from 0.163 to 0.007 (mean 0.054). The majority of the 100 articles were research articles (67%) and published from 1996 to 2000 (30%). The author and journal with the largest share of these 100 articles were Stephen M. Smith (n = 6) and Science (n = 13) respectively. Among the 100 most-cited articles, 37 were interlinked via citations of one another, and they could be classified into five major topics, four of which were scientific topics, namely neurological disorders, prefrontal cortex/emotion/reward, brain network, and brain mapping. The remaining topic was methodology. Interestingly 41 out of 63 of the rest, non-interlinked articles could also be categorized under the above five topics. Adjusted journal impact factor among these 100 articles did not appear to be associated with the corresponding adjusted citation count.

Conclusion: The current study compiles a comprehensive list and analysis of the 100 most-cited articles relevant to neuroscience that enables the comprehensive identification and recognition of the most important and relevant research topics concerned.

“At the Leading Front of Neuroscience: A Bibliometric Study of the 100 Most-Cited Articles” by Andy W. K. Yeung, Tazuko K. Goto and W. Keung Leung in Frontiers in Human Neuroscience. Published online July 21 2017 doi:10.3389/fnhum.2017.00363

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