Theories of motor control postulate that the brain uses internal models of the body to control movements accurately. Internal models are neural representations of how, for instance, the arm would respond to a neural command, given its current position and velocity. Previous studies have shown that the cerebellar cortex can acquire internal models through motor learning. Because the human cerebellum is involved in higher cognitive function as well as in motor control, we propose a coherent computational theory in which the phylogenetically newer part of the cerebellum similarly acquires internal models of objects in the external world. While human subjects learned to use a new tool (a computer mouse with a novel rotational transformation), cerebellar activity was measured by functional magnetic resonance imaging. As predicted by our theory, two types of activity were observed. One was spread over wide areas of the cerebellum and was precisely proportional to the error signal that guides the acquisition of internal models during learning. The other was confined to the area near the posterior superior fissure and remained even after learning, when the error levels had been equalized, thus probably reflecting an acquired internal model of the new tool.

We studied the neural correlates of visuomotor sequence learning using functional magnetic resonance imaging (fMRI). In the test condition, subjects learned, by trial and error, the correct order of pressing two buttons consecutively for 10 pairs of buttons (2 x 10 task); in the control condition, they pressed buttons in any order. Comparison between the test condition and the control condition revealed four brain areas specifically related to learning: the dorsolateral prefrontal cortex (DLPFC), the presupplementary motor area (pre-SMA), the precuneus, and the intraparietal sulcus (IPS). We found that the time course of activation during learning was different between these areas. To normalize the individual differences in the speed of learning, we classified the performance of each subject into three learning stages: early, intermediate, and advanced stages. Both the relative increase of signal intensity and the number of activated pixels within the four areas showed significant changes across the learning stages, with different time courses. The two frontal areas, DLPFC and pre-SMA, were activated in the earlier stages of learning, whereas the two parietal areas, precuneus and IPS, were activated in the later stages. Specifically, DLPFC, pre-SMA, precuneus, and IPS were most highly activated in the early stage, in both the early and intermediate stages, in the intermediate stage, and in both the intermediate and advanced stages, respectively. The results suggest that the acquisition of visuomotor sequences requires frontal activation, whereas the retrieval of visuomotor sequences requires parietal activation, which might reflect the transition from the declarative stage to the procedural stage.

Spatial attention was studied using a new visual ilhrsion of motion: a line, which was presented physically at once, was perceived to be drawn from one side when attention had been captured to that side of the line by a preceding visual cue stimulus. By comparing with a temporal order task, we showed that the line-motion illusion was produced by acceleration of visual information processing at the locus of attention. The results suggest that the facilitatory effect of attention is exerted at relatively early stages of visual information processing where visual signals are to be fed into the motion detecting mechanism.

Human capabilities in dexterously manipulating many different tools suggest modular neural organization at functional levels, but anatomical modularity underlying the capabilities has yet to be demonstrated. Although modularity in phylogenetically older parts of the cerebellum is well known, comparable modularity in the lateral cerebellum for cognitive functions remains unknown. We investigated these issues by functional MRI (fMRI) based on our previous findings of a cerebellar internal model of a tool. After subjects intensively learned to manipulate two novel tools (the rotated mouse whose cursor appeared at a rotated position, and the velocity mouse whose cursor velocity was proportional to the mouse position), they could easily switch between the two. The lateral and posterior cerebellar activities for the two different tools were spatially segregated, and their overlaps were <10%, even at low statistical thresholds. Activities of the rotated mouse were more anterior and lateral than the velocity mouse activities. These results were consistent with predictions by the MOdular Selection And Identification Controller (MOSAIC) model that multiple internal models compete to partition sensory-motor experiences and their outputs are linearly combined for a particular context.

Attention may be drawn passively to a visually salient object. We may also actively direct attention to an object of interest. Do the two kinds of attention, passive and active, interact and jointly influence visual information processing at some neural level? What happens if the passive and active attentions come into conflict? These questions were addressed with the aid of a novel psychophysical technique which reveals an attentional gradient as a sensation of motion in a line which is presented instantaneously. The subjects were asked to direct attention with voluntary effort: to the side opposite to a stimulus change, to an object with a predetermined colour, and to an object moving smoothly. In every case the same motion sensation was induced in the line from the attended side to the unattended side. This voluntary attention, however, can easily and quickly be distracted by a change in the periphery, though it can be regained within a period of 200 to 500 ms. The results suggest that the line motion can be induced in voluntary (top-down) as well as stimulus-driven (bottom-up) situations, thus indicating the truly attentional nature of the effect, rather than it being some kind of retinotopic sensory artifact or response bias. The results also suggest that these two kinds of attention have facilitatory effects acting together on a relatively early stage of visual information processing.