Content area
Abstract
Choosing one's preferred hypothesis requires multiple brain regions to work in concert as a functionally connected network. We predicted that a stronger network signal would underlie cognitive coherence between a hypothesis and the available evidence. In order to identify such functionally connected networks in magnetoencephalography (MEG) data, we first localized the generators of changes in oscillatory power within three frequency bands, namely alpha (7-13Hz), beta (18-24Hz), and theta (3-7Hz), with a spatial resolution of 5mm and temporal resolution of 50ms. We then used principal component analysis (PCA) to identify functionally connected networks reflecting co-varying post-stimulus changes in power. As predicted, PCA revealed a functionally connected network with a stronger signal when the evidence supported accepting the hypothesis being judged. This difference was driven by beta-band power decreases in the left dorsolateral prefrontal cortex (DLPFC), ventromedial prefrontal cortex (VMPFC), posterior cingulate cortex (PCC), and midline occipital cortex.