The effect of feedback on non-motor probabilistic classification learning in Parkinson's disease

It has been proposed that procedural learning is mediated by the striatum and, it has been reported that patients with Parkinson's disease (PD) are impaired on the weather prediction task (WPT) which involves probabilistic classification learning with corrective feedback (FB). However, PD patients were not impaired on probabilistic classification learning when it was performed without corrective feedback, in a paired associate (PA) manner; suggesting that the striatum is involved in learning with feedback rather than procedural learning per se. In Experiment 1 we studied FB- and PA-based learning in PD patients and controls and, as an improvement on previous methods, used a more powerful repeated measures design and more equivalent test phases during FB and PA conditions (including altering the FB condition to remove time limits on responding). All participants (16 PD patients, H&Y I–III and 14 matched-controls) completed the WPT under both FB and PA conditions. In contrast to previous results, in Experiment 1 we did not find a selective impairment in the PD group on the FB version of the WPT relative to controls. In Experiment 2 we used a between groups design and studied learning with corrective FB in 11 PD patients (H&Y I.5–IV) and 13 matched controls on a more standard version of the WPT similar to that used in previous studies. With such a between groups design for comparison of FB and PA learning on the WPT in PD, we observed impaired learning in PD patients relative to controls across both the FB and PA versions of the WPT. Most importantly, in Experiment 2 we also failed to find a selective impairment on the FB version of the WPT coupled with normal learning on the PA version in PD patients relative to controls. Our results do not support the proposal that the striatum plays a specific role in probabilistic classification learning with feedback.