|
内容記述 |
Dopamine’s influence on large-scale network dynamics, especially on the default mode network (DMN), remains uncertain, as fMRI studies have produced mixed results. One likely contributor to these discrepancies is reliance on traditional functional connectivity analyses, which typically derive a single metric (e.g., the Pearson correlation coefficient) from the entire time series and thus fail to capture network dynamics. To address this issue, we combined a dopaminergic challenge (mazindol, a dopamine transporter [DAT] reuptake inhibitor), PET, resting-state fMRI, and hidden Markov modeling (HMM) to characterize time-varying alterations in human large-scale functional networks following acute DAT blockade. We found that mazindol-induced increases in endogenous dopamine altered the balance between the brain’s functional “metastates,” two recurrent higher-order network configurations that each encompass multiple HMM-derived brain states. Mazindol increased the time participants spent in an internally oriented cognitive metastate and decreased the time spent in a sensorimotor–perceptual metastate, with the DMN showing the most pronounced lengthening. In exploratory analyses, declines in [¹¹C]raclopride binding, a PET index of D2 dopamine receptor availability reflecting increased striatal extracellular dopamine levels, tended to show a positive correlation with the prolongation of these cognitive states. These findings indicate that dopamine is closely linked to shifts from sensorimotor and perceptual to cognitive brain metastates, potentially underpinning the prioritization of internally oriented over externally driven psychological processes. Our results highlight the importance of dynamic, time-resolved connectivity approaches for understanding neuromodulatory actions in the human brain and suggest that dopamine helps regulate the dynamic balance between functionally competing large-scale brain networks. |
