Mapping topography and network of brain injury in patients with disorders of consciousness

• Published in: Frontiers in neurology Vol. 14; p. 1027160
• Main Authors: Liyana Arachige, Manoj, Seneviratne, Udaya, John, Nevin, Ma, Henry, Phan, Thanh G.
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 29.03.2023
• Subjects: disorders of consciousness; graph theory; neuroanatomy; Neurology; non-negative matrix factorisation; text mining; disorders of consciousness; non-negative matrix factorisation; text mining; neuroanatomy; graph theory
• ISSN: 1664-2295; 1664-2295
• DOI: 10.3389/fneur.2023.1027160

There is a growing interest in the topography of brain regions associated with disorders of consciousness. This has caused increased research output, yielding many publications investigating the topic with varying methodologies. The objective of this study was to ascertain the topographical regions of the brain most frequently associated with disorders of consciousness. We performed a cross-sectional text-mining analysis of disorders of consciousness studies. A text mining algorithm built in the Python programming language searched documents for anatomical brain terminology. We reviewed primary PubMed studies between January 1st 2000 to 8th February 2023 for the search query "Disorders of Consciousness." The frequency of brain regions mentioned in these articles was recorded, ranked, then built into a graphical network. Subgroup analysis was performed by evaluating the impact on our results if analyses were based on abstracts, full-texts, or topic-modeled groups (non-negative matrix factorization was used to create subgroups of each collection based on their key topics). Brain terms were ranked by their frequency and concordance was measured between subgroups. Graphical analysis was performed to explore relationships between the anatomical regions mentioned. The PageRank algorithm (used by Google to list search results in order of relevance) was used to determine global importance of the regions. The PubMed search yielded 24,944 abstracts and 3,780 full texts. The topic-modeled subgroups contained 2015 abstracts and 283 full texts. Text Mining across all document groups concordantly ranked the thalamus the highest (Savage score = 11.716), followed by the precuneus (Savage score = 4.983), hippocampus (Savage score = 4.483). Graphical analysis had 5 clusters with the thalamus once again having the highest PageRank score (PageRank = 0.0344). The thalamus, precuneus and cingulate cortex are strongly associated with disorders of consciousness, likely due to the roles they play in maintaining awareness and involvement in the default mode network, respectively. The findings also suggest that other areas of the brain like the cerebellum, cuneus, amygdala and hippocampus also share connections to consciousness should be further investigated.