We then fit the data with a polynomial (dashed curve in Figure 3B; see Experimental Procedures) and used its peaks and troughs to determine the approximate locations of the boundaries between adjacent cortical areas. Based on this analysis, we conceptually divided the recording sites on STP into four sectors, which we estimate correspond to the following subdivisions within the auditory cortex: Sec (sector) 1, A1/ML; Sec 2, R/RL;

Sec 3, RTL; Sec 4, RTp (Figure 3A). The www.selleckchem.com/products/BKM-120.html core/belt (e.g., A1/ML) boundary within Sec 1 or Sec 2 could not be determined by changes in the CF because the tuning frequency does not vary along the medial-lateral axis of the STP (e.g., Petkov et al., 2006). Nor could we detect the boundary with any certainty based on differences in sharpness or strength of tuning between the belt and the core (Rauschecker et al., 1995). We also examined maps obtained with other field potential frequency bands. Although the CF maps from the lower frequency bands (theta, alpha, beta, and low gamma) were similar to the map from the high-gamma band (Figure S1), it was more difficult

to discern clear reversals in the CF maps from the lower frequency bands. The difficulty is evident from inspection of the CF values projected on the caudorostral axis of the supratemporal plane (Figures S1A andS1B, right column). In the lower frequency bands, the CF values did not selleck screening library vary and reverse as smoothly as those in the high-gamma band. To quantify the difference, we examined how well a polynomial curve fit each of the CF maps projected on the caudorostral axis (the blue curves in the columns on the right in Figures S1A and S1B). We found that high gamma had the highest R2. Although high R2 values could be obtained from untuned data (i.e., without frequency tuning, all points could lie on a line and still be well fitted), it is clear from the plots that the drop in the value of R2 for the other evoked frequency bands was due to decreased Ketanserin consistency in tuning along the caudorostral axis. The results

indicate not only that the high-gamma band produced the clearest tonotopic maps, but also that the other frequency bands produced noisier, although consistent maps. To test this point further, we also examined the optimal degree of polynomials fit to the CFs using the Bayesian information criteria (BIC) (see Supplemental Experimental Procedures). The maps from the low frequency bands were fitted optimally with first- or second-order polynomials (Table S1: theta and beta bands in monkey M; theta, alpha, beta, and low-gamma bands in monkey B, see Supplemental Experimental Procedures), suggesting that the data from these frequency bands were not structured enough to have the multiple mirror symmetric reversals evident in data from the highest frequency band.