(ProQuest: ... denotes formulae omitted.)Language and music are interesting to psychology because they have been claimed to be two of the few uniquely human abilities. Much has been made of both their similarities and differences, and despite the many ways in which language and music have been demonstrated to be modular, cases of overlap or influence between the two abound. Understanding this influence is key to understanding the function of each, and will perhaps lend more general insight into the architecture of the human perceptual system.This study focuses on crossover between language and music at the auditory or phonetic level, examining the use of pitch in music and lexical tone language. Recent evidence suggests that crossover effects between these domains are bidirectional (Bidelman, Hutka, & Moreno, 2013); musicianship influences the perception of tone, and tone language experience influences music perception. The experiment presented here aims to contribute additional evidence for the latter direction, as well as to go beyond already demonstrated effects by describing the nature of such crossover based on perceptual features of lexical tone and musical melody.BackgroundScope of Language-Music OverlapThe OPERA hypothesis (Patel, 2011) explains the influence of music on speech perception as resulting from a combination of the neural overlap of acoustic processing and the task demands of musical training (e.g., repetition). These acoustic and task characteristics, however, are not unique to music, so OPERA does not rule out bidirectional effects, but rather points out why in some cases one direction of influence (as described by Patel, 2011, music to language) may be more prevalent; but whichever domain is more cognitively demanding in some aspect (e.g., precision of acoustic or temporal categories) may be expected to influence the other.OPERA and similar models assert that music and language share neural resources for processing and learning common features, such as sound categories and hierarchical structures, rather than of musical or linguistic categories per se. Besson, Chobert, and Marie (2011) make a distinction between shared acoustic processing and memory- or attention-driven training effects, and although it is likely that there is more than one way in which language and music influence one another, even higherlevel effects related to specific linguistic or musical knowledge involve perceptual (rather than abstract) representations, or the way in which perceptual resources are deployed in musical and linguistic tasks. The common thread of such models is that they do not necessitate a total overlap between perceptual resource networks for musical and linguistic pitch, nor that crossover effects be entirely symmetrical. Instead, they predict that crossover effects occur in ways predictable from the content and context of learning (Bradley, 2013).Although the mechanisms of transfer are not fully understood, several neural processes have been proposed to explain how such crossover takes place, notably Reverse Hierarchy Theory (RHT) (Ahissar & Hochstein, 2004; Ahissar, Nahum, Nelken, & Hochstein, 2009), invoked by Kraus and Banai (2007), and tuning via the corticofugal pathway (Wong, Skoe, Russo, Dees, & Kraus, 2007). The key features of such models are that rather different cognitive tasks may share a reliance on similar sensory input, and top-down feedback tunes sensory resources which are domaingeneral, and therefore available to other tasks in the absence of direct training (Bradley, 2014). These principles are supported by the overlap of speech and song activation in temporal cortical areas (associated with the encoding basic properties of stimuli), relative to frontal and parietal regions associated with task-specific representations (Merrill et al., 2012). This diverges from some earlier models in which pitch processing for music diverges early from that of other auditory tasks (Peretz & Coltheart, 2003; Zatorre, Belin, & Penhune, 2002), but is consistent with developmental theories linking music and language learning to more general learning mechanisms (McMullen & Saffran, 2004; Trehub & Hannon, 2006). …