Language content and action/perception have been shown to activate common brain areas in previous neuroimaging studies. However, it is unclear whether overlapping cortical activation reflects a common neural source or adjacent, but distinct, sources. We address this issue by using multivoxel pattern analysis on fMRI data. Specifically, participants were instructed to engage in five tasks: (1) execute hand actions (AE), (2) observe hand actions (AO), (3) observe nonbiological motion (MO), (4) read action verbs, and (5) read nonaction verbs. A classifier was trained to distinguish between data collected from neural motor areas during (1) AE versus MO and (2) AO versus MO. These two algorithms were then used to test for a distinction between data collected during the reading of action versus nonaction verbs. The results show that the algorithm trained to distinguish between AE and MO distinguishes between word categories using signal recorded from the left parietal cortex and pre-SMA, but not from ventrolateral premotor cortex. In contrast, the algorithm trained to distinguish between AO and MO discriminates between word categories using the activity pattern in the left premotor and left parietal cortex. This shows that the sensitivity of premotor areas to language content is more similar to the process of observing others acting than to acting oneself. Furthermore, those parts of the brain that show comparable neural pattern for action execution and action word comprehension are high-level integrative motor areas rather than low-level motor areas.

Although much is known about decision making under uncertainty when only a single step is required in the decision process, less is known about sequential decision making. We carried out a stochastic sequence learning task in which subjects had to use noisy feedback to learn sequences of button presses. We compared flat and hierarchical behavioral models and found that although both models predicted the choices of the group of subjects equally well, only the hierarchical model correlated significantly with learning-related changes in the magneto-encephalographic response. The significant modulations in the magneto-encephalographic signal occurred 83 msec before button press and 67 msec after button press. We also localized the sources of these effects and found that the early effect localized to the insula, whereas the late effect localized to the premotor cortex.