Neuroarchitecture Assessment: An Overview and Bibliometric Analysis

Abstract

Research on the relationship between architecture and neuroscience has increased in number and significance since the 1990s. Although a growing number of studies revolve around this field of research, there are very limited studies that have reviewed and assessed the field and there is a gap in the literature to address the overall analysis of neuroarchitecture literature and its evolution. Additionally, neuroarchitecture literature is now challenging to manage because of its multidisciplinary scope and wide range spread within different themes and journals. The primary aim of this study is to present a bibliometric analysis of three decades of research on neuroarchitecture. This provides an overall picture of the field and its research landscape. Two hundred and ninety-five publications were included in the final database of the study after screening processes. Next, a science mapping tool, VOSviewer, was utilized to detect major topics as well as influential authors, countries, publications, and prominent journals using different network analysis techniques such as term co-citation, term co-occurrence, and bibliographic coupling. Next, a similar co-occurrence analysis was conducted to identify the major themes and the evolution of the intellectual basis of the field. SciMAT was also used to detect how the intellectual base of the knowledge in the field has evolved over time. It also assisted to identify the major themes that have contributed to this evolution. The results show that this field has initially been mainly focused on few themes but has later become more diversified to acknowledge the multi-faceted characteristics of neuroarchitecture; over time, the intellectual base of the field of neuroarchitecture started to grow, particularly from 2016. Major progress in the development of theoretical and methodological approaches has been achieved and there has been a paradigm shift toward major keywords in neuroarchitecture such as EEG, fMRI, and virtual reality.