8) and vocal sounds as deviants (P = 02), while the reverse was

8) and vocal sounds as deviants (P = 0.2), while the reverse was true for the other two blocks. In each block, standards always consisted of just one token of one sound category (for example, just a female voice), while deviants consisted of both tokens of the opposite sound category (for example, a cello and a French Horn). Both tokens of the deviant sounds occurred this website equiprobably (P = 0.1 each). Both standards and deviants were of two durations – 350 and 550 ms, with each duration occurring equiprobably (P = 0.5). The 200-ms difference between short and long sounds used in the current study is similar to that used in previous studies employing the auditory distraction paradigm (e.g. Schröger

& Wolff, 2000; Mager et al., 2005). STA-9090 clinical trial Each block consisted of 200 trials (160 standards and 40 deviants). The inter-stimulus interval varied randomly between 1.6 and 2 s. The ROT condition was identical to the NAT condition, with the only difference being that spectrally-rotated versions of voices and musical sounds were used throughout. Table 1 lists all conditions and blocks of the study. Figure 2 details the structure of a single block. The eight blocks of the experiment were presented in a Latin square design, lasting approximately 6 min each. Participants were instructed to press one

response button for short sounds and another for long sounds. Three examples of short and three of long sounds present in each block were always played at the beginning of a block to familiarize participants with the sounds they were instructed to categorize. Hand to response button mapping was counterbalanced across participants. Importantly, unlike in odd-ball paradigms, responses were provided for all sounds (i.e. standards and deviants). The N1 ERP component elicited by the onset of auditory stimuli was evaluated in order to compare the two groups’ early neural processing of musical and vocal sounds. N1 is a measure of early sensory encoding of the physical properties of sound, such as frequency, complexity and intensity

(Näätänen & Picton, 1987). Importantly, previous ERP research has demonstrated the influence of musical training on the amplitude of N1 and its N1c subcomponent. For example, it has been shown to be enhanced in musicians during in response to both musical notes and pure tones, with greater enhancement for the sounds of the instrument of training (e.g. Pantev et al., 1998, 2001; Shahin et al., 2003; Baumann et al., 2008). We therefore predicted that musicians would exhibit a larger N1 component to musical sounds. We also speculated that given the similarity of vocal and musical timbres and their underlying acoustic properties, musicians might also show an enhanced N1 to voices. Additionally, we have evaluated several behavioral and electrophysiological measures associated with distraction.

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