Frontiers in Neuroscience · 2017 · 23 citations · 4 references
Life SciencesNeurobiologyNeuroscienceMolecular NeuroscienceNetwork BiologySystems NeuroscienceBrain ConnectivityBrain ImagingBrain Network AnalysisCortical NetworksFunctional ConnectivityFunctional NeuroimagingFunctional Brain ConnectivityFunctional Brain NetworksFunctional Magnetic Resonance ImagingFunctional Magnetic Resonance Imaging CorrelatesProximityResting-state Cortical Networks
A recent report claims that functional brain networks defined with resting-state functional magnetic resonance imaging (fMRI) can be recapitulated with correlated gene expression (i.e., high within-network tissue-tissue "strength fraction," SF) (Richiardi et al., 2015). However, the authors do not adequately control for spatial proximity. We replicated their main analysis, performed a more effective adjustment for spatial proximity, and tested whether "null networks" (i.e., clusters with center coordinates randomly placed throughout cortex) also exhibit high SF. Removing proximal tissue-tissue correlations by Euclidean distance, as opposed to removing correlations within arbitrary tissue labels as in Richiardi et al. (2015), reduces within-network SF to no greater than null. Moreover, randomly placed clusters also have significantly high SF, indicating that high within-network SF is entirely attributable to proximity and is unrelated to functional brain networks defined by resting-state fMRI. We discuss why additional validations in the original article are invalid and/or misleading and suggest future directions.
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