Construction And Analysis Of The Time-Evolving Pain-Related Brain Network Using Literature Mining

Journal of Pain Research Dovepress open access to scientific and medical research Open Access Full Text Article ORIGINAL RESEARCH Construction And Analysis Of The Time-Evolving Pain-Related Brain Network Using Literature Mining This article was published in the following Dove Press journal: Journal of Pain Research Jihong Oh Hyojin Bae Chang-Eop Kim Department of Physiology, College of Korean Medicine, Gachon University, Seongnam 13120, Republic of Korea Purpose: We aimed to quantitatively investigate how the neuroscience field developed over time in terms of its concept on how pain is represented in the brain and compare the research trends of pain with those of mental disorders through literature mining of accumulated published articles. Methods: The abstracts and publication years of 137,525 pain-related articles were retrieved from the PubMed database. We defined 22 pain-related brain regions that appeared more than 100 times in the retrieved abstracts. Time-evolving networks of pain-related brain regions were constructed using the co-occurrence frequency. The state-space model was implemented to capture the trend patterns of the pain-related brain regions and the patterns were compared with those of mental disorders. Results: The number of pain-related abstracts including brain areas steadily increased; however, the relative frequency of each brain region showed different patterns. According to the chronological patterns of relative frequencies, pain-related brain regions were clustered into three groups: rising, falling, and consistent. The network of pain-related brain regions extended over time from localized regions (mainly including brain stem and diencephalon) to wider cortical/ subcortical regions. In the state-space model, the relative frequency trajectory of pain-related brain regions gradually became closer to that of mental disorder-related brain regions. Conclusion: Temporal changes of pain-related brain regions in the abstracts indicate that emotional/cognitive aspects of pain have been gradually emphasized. The networks of painrelated brain regions imply perspective changes on pain from the simple percept to the multidimensional experience. Based on the notable occurrence patterns of the cerebellum and motor cortex, we suggest that motor-related areas will be actively explored in pain studies. Keywords: pain, pain-related brain regions, pain-related brain networks, pain research trend analysis, literature mining, text mining, mental disorders and pain Introduction Correspondence: Chang-Eop Kim Department of Physiology, College of Korean Medicine, Gachon University, 1342, Seongnam-daero, Sujeong-gu, Seongnam-si, Gyeonggi-do, Repubic of Korea Tel/fax +82-31-750-5416 Email submit your manuscript | www.dovepress.com DovePress http://doi.org/10.2147/JPR.S217036 Over the decades, enormous basic and clinical study efforts have led to many advances in the understanding of pain mechanism, and researchers have expanded their knowledge on the complex and multidimensional characteristics of pain.1–3 In the early investigation of the brain mechanism of pain, efforts have been made to find a single brain area responsible for pain perception, as in the other sensory modality of vision or hearing. However, it turned out that pain is multidimensional experience emerging from the integrated activity of the brain and there is no single region such as “primary pain cortex”. Numerous neuroimaging studies have demonstrated that multiple brain regions are involved in various pain conditions. While several brain regions such as the Journal of Pain Research 2019:12 2891–2903 2891 © 2019 Oh et al. This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). Dovepress Oh et al thalamus, insula, and ACC have been consistently reported to be activated during acute nociception regardless of the type of noxious stimuli, brain activity patterns for chronic pain are rather heterogeneous within and across different chronic pain conditions. However, studies from both acute and chronic pain have highlighted the emotional and cognitive aspects in pain perception regardless of the pain types.4–10 Furthermore, accumulated evidence has indicated interactions between mental disorders and acute/ chronic pain.11–15 Recently, a new perspective was suggested which states that pain perception is associated with the negative moods (eg, anxiety and depression) as a continuum of aversive behavioral learning.16 There are hundreds of thousands of accumulated articles about pain so far. Many researchers have reviewed the activity of diverse brain regions involved in various pain conditions to understand the brain mechanisms of pain perception. However, it is practically limited for the researchers to manually investigate a vast number of papers and draw quantitative results efficiently. It also might be possible to obtain biased results according to the researcher’s background knowledge or research interests. Recently, the literature mining approach has been actively applied in various biomedical fields to efficiently extract scientific knowledge from the accumulated data.17–25 Literature mining converts unstructured textual information into structured data to extract meaningful numeric information and find patterns.26,27 The advantage of literature mining is that it can quickly analyze vast quantities of documents and mine the latent knowledge such as the implicit relationships between the words by computing quantitative metrics, eg, the frequency of occurrence and co-occurrence between words. In this study, we aimed to quantitatively investigate how the neuroscience field developed over time in terms of its concept on how pain is represented in the brain and compare the research trends of pain with those of mental disorders through literature mining of accumulated published articles. First, the bibliographic information of 137,525 pain-relevant abstracts was retrieved from PubMed and then preprocessed. The brain regions were automatically recognized from the abstracts. Subsequently, we performed frequency and cooccurrence analyses to identify the temporal pattern of the occurrences of pain-related brain regions. Relative frequency patterns of pain-related brain regions were compared with those of mental disorders-related brain regions. Evolving occurrence patterns of the pain-related brain regions were investigated through the network (...truncated)