Background: Cognitive science is an interdisciplinary field whose methodology is less developed in the form of books or independent articles and there are many problems in its methodological field.
Aims: The aim of this research was to study the methodological content and statistical analysis of articles related to cognitive sciences.
Methods: The articles were examined by content analysis method. The study population is all the articles related to the field of cognitive sciences that have been indexed in the ranking website of scientific journals in 2016 and the sampling method is purposeful. In order to classify the techniques and methods adopted from content analysis, a square matrix related to these techniques was provided to 7 experts in the field of cognitive science methodology and they were asked to rate their views on the similarity of each of these techniques and methods on a scale of 100 points. The mean score obtained from these matrices was entered into R software as similarity matrix with the aim of discovering clusters, The Fruchterman-Ringold algorithm was used to visualize the relationship between the different techniques.
Results: Content analysis of articles and inclusion of related keywords in the coding sheet led to a list of statistical methods. The graph obtained from the network of conections between statistical techniques and methods with significant distances was drawn (p≤0.001).
Conclusion: Close-up techniques in the resulting graph were examined in detail and finally the methods used to analyze cognitive data in 17 clusters were introduced, the main purpose of the techniques used in each cluster was determined and research on how to select these techniques was suggested.