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The regression analysis including the four predictor variables (IQ, sound processing, and the two musical training variables) explained 28.7% (adjusted R2) of the variance in BAT score [F(4,51) = 6.523, p performance in WS. The multilevel binomial models confirmed the significant selleck compound individual variability in BAT performance in both the WS [��2(58) = 141.31, p Veliparib solubility dmso excerpt, an orchestral pops version of the Superman theme. The beat of this stimulus was more than twice as variable (CV = 7.8%) as the next most variable stimulus (an orchestral pops rendition of Richard Rogers waltzes CV = 3.7%) or the average of all other stimuli included in our test battery (CV = 2.7%). When this item was excluded, beat variability was no longer a significant predictor of item accuracy. Instead, orchestral pops stimuli (versus rock stimuli) were associated with only a 71.3% chance of a correct answer [t(761) = -2.049, p = 0.041, OR = 0.62] when controlling for tempo and beat variability. Table 3 Multilevel model predicting item accuracy on DDR1 the BAT in WS (n = 59). Table 4 Multilevel model predicting item accuracy on the BAT in TD (n = 35). In contrast, in TD participants, tempo and jazz genres were significant predictors of accuracy. A 1 ms increase in inter-onset-interval of the beat (i.e., slower tempo) was associated with a 90.8% chance of correctly answering a BAT item while jazz stimuli (versus rock stimuli) were associated with an 83% chance of correctly answering a BAT item. Montreal Battery of Evaluation of Amusia Meter Subtest As depicted in Figure ?Figure11, there were vast individual differences in meter perception in both the WS and TD groups though overall performance was significantly greater in the TD (mean = 26.92 �� 3.5, median = 28) than WS (mean = 24.43 �� 5.1, median = 26) group (Mann�CWhitney U = 1333, p = 0.004). Among WS participants, greater MBEA-m performance was associated with higher IQ (�� = 0.342, p = 0.003), number of lesson types (�� = 0.413, p