抄録
An internal model is a neural mechanism that can mimic the input-output properties of a controlled object such as a tool. Recent interests have moved on to how multiple internal models are learned and switched under a given context. Two representative computational models for switching propose distinct neural mechanisms, thus predicting different brain-activity patterns in the switching of internal models. In one model, called the mixture-of-experts architecture, switching is commanded by a single executive called a "gating network," which is different from the internal models. In the other model, called the MOSAIC, the internal models themselves play crucial roles in switching. Consequently, the mixture-of-experts model predicts that neural activities related to switching and internal models can be temporally and spatially segregated, while the MOSAIC predicts that they are closely intermingled. Here, we examined the two predictions by analyzing fMRI activities during the switching of one common tool and two novel tools. The switching and internal-model activities temporally and spatially overlapped each other in the cerebellum and in the parietal cortex whereas the overlap was very small in the frontal cortex. These results suggest that 1) switching mechanisms in the frontal cortex can be explained by the mixture-of-experts model, while those in the cerebellum and the parietal cortex are explained by the MOSAIC, or 2) the prefrontal regions estimates contribution of each internal model, and gives the cerebellum feedback within the MOSAIC. Supported by the TAO. [Jpn J Physiol 54 Suppl:S51 (2004)]
