A positive d′ in both conditions indicates units/sites that retained their preference in the BFS, while a negative d′ in the BFS condition indicates units/sites that fired more when their preferred stimulus was perceptually suppressed. Statistically significant modulations for each unit/site were identified by using a Wilcoxon rank-sum test to compare the two response distributions (consisting of the total number

of spike counts from t = 1,001–2,000 for the preferred and the nonpreferred stimuli, across all trials). Where appropriate, p values were corrected (and converted to q values) using the FDR method ( Benjamini & Hochberg (1995)). The PSD of the raw LFP signals from t = 1,001 to t = 2,000 ms was estimated using the multitaper method (Thomson, 1982). This method uses linear or nonlinear combinations of modified periodograms to estimate the check details PSD. These periodograms

are computed using a sequence of orthogonal tapers (windows in the frequency domain) specified from the discrete prolate spheroidal sequences. Selectivity of spectral power was computed using the d′ for narrow frequency bins of 1 Hz (d′sensory LFP and d′perceptual LFP) for sites where MUA exhibited significant sensory selectivity. Time frequency analysis was carried out by computing a spectrogram in each trial using overlapping (94%) 256 ms windows and then averaged across all trials. This study was supported by the Max Planck Society. GSK J4 ic50 We thank Drs. Andreas Tolias, Christoph Kayser, Kevin Whittingstall, and Michel Besserve for helpful discussions and comments on a previous version of the manuscript. Joachim Werner and Axel Oeltermann

provided excellent technical support. “
“Motor-sequence learning refers to the process by which temporally ordered movements are prepared and executed with increasing speed and accuracy (Willingham, 1998). For this type of learning to occur, the processing demands associated with the rapid planning of multiple serial movements within a sequence must be reconciled. The traditional notion is that the individual motor commands that constitute new sequences ever become temporally integrated into elementary memory structures or “chunks” (Gallistel, 1980, Lashley, 1951 and Book, 1908). Chunking in motor sequencing allows groups of individual movements to be prepared and executed as a single motor program facilitating the performance of complex and extended sets of sequences at lower cost (Halford et al., 1998). The grouping of distinct elements into a single unit is a general performance strategy that is also observed in nonmotor tasks (Gobet and Simon, 1998 and Ericsson et al., 1980).