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. 2008 Aug;14(6):457-64.
doi: 10.1016/j.parkreldis.2007.11.009. Epub 2008 Mar 3.

Implicit and explicit aspects of sequence learning in pre-symptomatic Huntington's disease

Affiliations

Implicit and explicit aspects of sequence learning in pre-symptomatic Huntington's disease

M F Ghilardi et al. Parkinsonism Relat Disord. 2008 Aug.

Abstract

Learning deficits may be part of the early symptoms of Huntington's disease (HD). Here we characterized implicit and explicit aspects of sequence learning in 11 pre-symptomatic HD gene carriers (pHD) and 11 normal controls. Subjects moved a cursor on a digitizing tablet and performed the following tasks: SEQ: learning to anticipate the appearance of a target sequence in two blocks; VSEQ: learning a sequence by attending to the display without moving for one block, and by moving to the sequence in a successive block (VSEQ test). Explicit learning was measured with declarative scores and number of anticipatory movements. Implicit learning was measured as a strategy change reflected in movement time. By the end of SEQ, pHD had a significantly lower number of correct anticipatory movements and lower declarative scores than controls, while in VSEQ and VSEQ test these indices improved. During all three tasks, movement time changed in controls, but not in pHD. These results suggest that both explicit and implicit aspects of sequence learning may be impaired before the onset of motor symptoms. However, when attentional demands decrease, explicit, but not implicit, learning may improve.

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Figures

Figure 1
Figure 1
Average values (±S.E.) for pHD subjects and normal controls are shown as black and white columns, respectively. A. Predictable timed response sequence (CCW). Onset times occurred later (F(1,10)=9.4, p<0.007) and movement times were shorter (F(1,10)=4.9, p<0.05) in pHD than in controls. No differences between groups were found for timing error (F(1,10) = 2.9, p=0.11). B. Movements to random targets (RAN). No differences were found between the two groups for reaction time, movement time, and spatial error.
Figure 2
Figure 2
Sequence learning in controls (empty symbols) and pHD (filled symbols). A. Onset time, plotted as a function of movement cycles, significantly decreases in SEQ1 (circles) but at more rapid pace in controls than in pHD. The group difference persisted in SEQ2 (diamonds). After visual exposure, pHD onset times for the sequence performed in VSEQtest (squares) were lower than SEQ2 (F(1,40)=4.9, p<0.05), but were still different than controls. B. Number of correct anticipatory movements per cycle increases during SEQ1 block with a significant difference between controls and pHD. Group differences were less evident in SEQ2 and VSEQ. In VSEQtest, the number of anticipatory movements was significantly higher than in SEQ2 only for the pHD group (F(1,40)=4.2, p<0.05). C. In normal subjects movement time increased during SEQ1 and further raise, although not significantly so, inSEQ2. In VSEQtest it increased similarly to SEQ1. In pHD, movement times of SEQ1 first cycle were not different from controls; however, unlike in controls, there was no increase in the course of either SEQ1, SEQ2 or VSEQtest blocks.
Figure 3
Figure 3
Mean declarative scores of controls and pHD after SEQ1 (empty columns) and VSEQ (black columns). ANOVA disclosed a significant effect of group (F(1,40)=20.0, p<0.0001) and task (F(1,40)=4.9, p=0.03) with a significant interaction group x task (F(1,40)=4.1, p<0.05). Post hoc test showed that there was a significant difference between SEQ1 and VSEQ in pHD (p=0.002), but not in controls. Moreover, there was a significant difference between controls and pHD for SEQ1 (p=0.0007), but not VSEQ.

References

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