In most studies, a particular stimulus feature is always associat

In most studies, a particular stimulus feature is always associated with a particular response and optimum performance is signified by the maximum possible d′ value GSK 3 inhibitor (typically between 3 and 4). Because of the family resemblance structure employed here, each feature was only associated with its typical category on 78% of trials. As a consequence, the optimum d′ score was lower: a participant classifying with 100% accuracy would have d′ scores of 1.52 for each dimension (indicated by the blue line in Fig. 4A). Scores higher than this indicate an over-extension of the learning in the strongest dimension, such that the information in this dimension was driving classification even for exemplars

where the other two dimensions pointed towards a different category. This over-generalisation was present in four of the seven patients and is similar to the over-generalisation exhibited by SD patients when attempting to use their impaired conceptual knowledge of real objects (see Discussion). No patients demonstrated much learning Small molecule library in their second or weakest dimensions, in line with the prediction that they would be unable to form category representations that integrated all of the information required for optimum categorisation. The mean d′ scores in each group can be seen in Fig. 4A. As expected, there was a

large disparity between the strongest dimension and the remaining two dimensions in SD, with a more balanced pattern of learning across the three dimensions in the control group. A 3 (dimension) × 2 (group) ANOVA was performed on these data. There was a main effect of dimension [F(2,34) = 43, p < .001]. There was no effect of group but there was a highly significant interaction between dimension and group [F(2,34) = 6.83, p = .003]. Post-hoc t-tests indicated that SD patients showed significantly less learning on their weakest dimension than controls [t(17) = 3.44, p = .003]. There was also a trend towards poorer learning on the second dimension in SD patients, relative to controls

[t(17) = 1.95, p = .07]. While the general pattern in the patient group was towards strong, single-dimension learning, we did observe some variation across patients, with J.W., N.H. and E.T. displaying a less clear pattern than the other four ADAMTS5 patients. To investigate these differences, we tested whether these patients’ responses were influenced by the shape colour dimension, which was irrelevant for classification. We calculated a d′ measure of “learning” in this dimension in a similar manner to the other dimensions. Since this dimension was irrelevant to classification, the optimum d′ was 0. The results are shown in Fig. 4B. The four patients who achieved the most successful learning on their strongest dimension showed low d′ values, indicating that they were not influenced by the irrelevant dimension. However, patients N.H. and E.T., and to a lesser extent J.W.

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