We present a general method for automatic meta-analyses in neuroscience and apply it on text data from published functional imaging studies to extract main functions associated with a brain area --- the posterior cingulate cortex. Abstracts from PubMed are downloaded, words extracted and converted to a bag-of-words matrix representation. The combined data is analyzed with hierarchical non-negative matrix factorization. We find that the prominent themes in the PCC corpus are episodic memory retrieval and pain. We further characterize the distribution in PCC of the Talairach coordinates available in some of the articles. This shows a tendency to functional segregation between memory and pain components where memory activations are predominantly in the caudal part and pain in the rostral part of PCC.
- text mining
- magnetic resonance imaging
Nielsen, F. Å., Balslev, D., & Hansen, L. K. (2005). Mining the posterior cingulate: Segregation between memory and pain components. NeuroImage, 27(3), 520-532. https://doi.org/10.1016/j.neuroimage.2005.04.034