Sequence Learning

Among the first motor learning tasks studied is the sequential tapping task, in which participants must tap the fingers of their dominant hand (all studies reviewed here used right-handed subjects) in a prespecified sequence. An early study scanned participants doing sequential finger tapping at three stages in the learning process. The three levels corresponded to an initial learning phase when a skill is first being learned, the phase when a skill becomes automatic after significant practice, and skilled performance after performance level has reached its asymptote. The ipsilateral (right) cerebellum was activated in all three conditions, and the activation per movement in the cerebellum decreased as training progressed. The striatum was also activated during advanced practice, suggesting a role for the basal ganglia in the development of automaticity.

Subsequent studies of sequential finger tapping have examined the role of the cerebellum and other structures, including changes in primary motor cortex, in more depth. Unpracticed performance activated a network of areas often associated with the planning and execution of movements: contralateral primary motor cortex and putamen, bilateral PMA and SMA (with more activity on the contralateral side), and cerebellum. With practice, activity decreased in the lateral portion and deep nuclei of the cerebellum, supporting the view that the cerebellum is important in sequence learning and may be less important in the execution of highly learned sequences.

Subsequent studies examined activations during a sequential finger-tapping task in which participants had to learn the correct sequence by trial and error. The first study compared activations between new sequences, learned sequences, and a resting control. Similar to the earlier studies, the performance of learned sequences with some degree of automaticity activated the contralateral (left) primary motor cortex, PMA, SMA, putamen, bilateral cerebellar hemispheres, vermis, deep cerebellar nuclei, anterior cingu-late, parietal cortex, and ventrolateral thalamus. Of course, because sequence performance was compared with a resting condition, this network includes areas responsible for processes irrelevant to sequence learning. When compared to rest, the performance of new sequences showed, in addition to these areas, increases in prefrontal cortex and more extensive activation of the cerebellum. When compared to the practiced sequence directly, learning of a new sequence produced activations in the bilateral PMA, cerebellum, anterior cingulate, prefrontal cortex, and medial thalamus. It seems likely that the requirement that the participant infer the correct sequence on the basis of feedback was responsible for the activation of the anatomically interconnected prefrontal-anterior cingulate-medial thalamus network. However, as we will see later, it is possible that the cerebellum also contributes to error detection and correction.

In another revealing manipulation, participants were asked to pay attention to their finger movements while performing a highly learned sequence. Attention resulted in the reactivation of the anterior cingulate and prefrontal cortex. By comparing learning of a new sequence with a control condition that required a similar level of attention and similar decision and motor processes, the researchers found activation of the caudate nucleus and cerebellum. This result indicates that these two structures may be important in learning a new sequence, as opposed to other task-related processes. Together, these studies suggest that the basal ganglia and cerebellum, and possibly the PMA, are involved in skill learning, whereas anterior cingulate and prefrontal areas are involved in attention and higher level control processes.

A more controlled version of the tapping task is the Repeated Sequence Task. In this task, participants see a cue appear above one of four squares, and they must touch that square as quickly as possible. As a particular sequence appears more frequently, participants become faster in pressing the appropriate squares. The faster responses for the learned sequence indicate that implicit learning of the sequence has occurred, even though participants have no explicit, declarative memory for the sequence.

Doyon and co-workers, using this paradigm, compared PET activation among several conditions, including different amounts of learning, and included a condition in which subjects were given explicit knowledge of the sequence prior to scanning. Performance on highly learned versus random sequences resulted in increased activation in the right (ipsilateral) ventral striatum, right cerebellum, bilateral anterior cingulate, right medial parietal cortex, and right extrastriate cortex. Decreases were found in the ventrolateral frontal, frontopolar, and lateral parietal cortices, all on the right side. As with previous studies, basal ganglia activity increased when performance was highly learned. These changes are consistent with animal models suggesting a role for the basal ganglia in the performance of movement sequences.

When compared with newly learned sequences, highly learned sequences showed increased activity in the cerebellum, suggesting a role for the cerebellum in sequence performance or in the development of automaticity. This finding contrasts with previous sequence learning studies, which found that cerebellar activity decreases as performance becomes automatic. Thus, further research is necessary to investigate the role of the cerebellum. It is possible that the cerebellum has multiple roles and plays a part both in initial learning and in later retrieval of sequences. An alternative explanation for cerebellar activity in the learned-unlearned comparisons in these studies is that the cerebellum is required for speeding up movements while maintaining a criterion level of accuracy. In the early stages of training, it may be difficult to keep movements speedy, resulting in cerebellar activation that decreases as it becomes easier to perform the task at the requisite speed. This hypothesis highlights the fact that neuroimaging results may be interpreted in multiple ways.

Newly and highly learned sequences in the Repeated Sequence Test were also examined before and after participants were given explicit knowledge of the sequence. Explicit knowledge of highly learned sequences relative to implicit performance decreased activation in the right (ipsilateral) cerebellum and increased activation in the right ventrolateral frontal cortex. Explicit versus implicit knowledge of newly learned sequences resulted in increased activation of the right cerebellum and left ventrolateral frontal cortex.

The sequence learning studies reviewed here implicate the cerebellum and basal ganglia in initial learning and automatization of new skills. Three studies found significant activity in the basal ganglia with practiced, but not novel, sequences. Two other studies found basal ganglia activity in newly learned sequences, one relative to a resting control and the other relative to a free-selection tapping task. The cerebellum appears to be involved in early learning of the sequence, but it is also active during skilled performance relative to rest. Its activity may increase as participants gain skill, if that skill involves making speeded responses to visual cues.

Notably, none of these PET studies showed changes in the primary motor cortex as a function of practice. However, some researchers have shown that skill learning produces nonmonotonic changes in the strength and spread of activation within the primary motor cortex. These researchers scanned participants learning one of two similar finger-tapping sequences using fMRI. Initially, a habituation effect to sequence performance was found: activity in the primary motor cortex was lower when it was performed later in the scanning block. After 30 min of practice, activity in the primary motor cortex was higher when it was performed later in the scanning block, but only for practiced sequences, possibly reflecting fast learning processes that set up later consolidation of a new motor sequence. After 4 weeks of daily practice, more areas in the primary motor cortex were recruited during performance of the learned sequence, showing that practice resulted in a true expansion of the cortical area recruited in the primary motor cortex.

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