Abstract
Music impacting on speech processing is vividly evidenced in most reports involving professional musicians, while the question of whether the facilitative effects of music are limited to experts or may extend to amateurs remains to be resolved. Previous research has suggested that analogous to language experience, musicianship also modulates lexical tone perception but the influence of amateur musical experience in adulthood is poorly understood. Furthermore, little is known about how acoustic information and phonological information of lexical tones are processed by amateur musicians. This study aimed to provide neural evidence of cortical plasticity by examining categorical perception of lexical tones in Chinese adults with amateur musical experience relative to the non-musician counterparts. Fifteen adult Chinese amateur musicians and an equal number of non-musicians participated in an event-related potential (ERP) experiment. Their mismatch negativities (MMNs) to lexical tones from Mandarin Tone 2–Tone 4 continuum and non-speech tone analogs were measured. It was hypothesized that amateur musicians would exhibit different MMNs to their non-musician counterparts in processing two aspects of information in lexical tones. Results showed that the MMN mean amplitude evoked by within-category deviants was significantly larger for amateur musicians than non-musicians regardless of speech or non-speech condition. This implies the strengthened processing of acoustic information by adult amateur musicians without the need of focused attention, as the detection of subtle acoustic nuances of pitch was measurably improved. In addition, the MMN peak latency elicited by across-category deviants was significantly shorter than that by within-category deviants for both groups, indicative of the earlier processing of phonological information than acoustic information of lexical tones at the pre-attentive stage. The results mentioned above suggest that cortical plasticity can still be induced in adulthood, hence non-musicians should be defined more strictly than before. Besides, the current study enlarges the population demonstrating the beneficial effects of musical experience on perceptual and cognitive functions, namely, the effects of enhanced speech processing from music are not confined to a small group of experts but extend to a large population of amateurs.
Highlights
Pertaining to the old relationship between music and language, it is believed that the spoken language evolves from music (Darwin, 1871), or music evolves from the spoken language (Spencer, 1857), or both of them descend from a common origin (Rousseau, 1781/1993)
No power analysis was performed for the calculation of sample size, the sample size of the current study was comparable with one seminal event-related potential (ERP) study by Xi et al (2010) that focused on the processing of acoustic versus phonological information via categorical perception of Mandarin lexical tones
Results of the ERP measurements indicated that both amateur musicians (AM) and NM groups provoked the significantly shorter mismatch negativities (MMNs) peak latency for across-category stimuli than within-category stimuli, which partially certifies our hypotheses of latency showing that these two types of information were processed concurrently but phonological information was processed prior to acoustic information of lexical tones at early pre-attentive stage, irrespective of speech or non-speech condition
Summary
Pertaining to the old relationship between music and language, it is believed that the spoken language evolves from music (Darwin, 1871), or music evolves from the spoken language (Spencer, 1857), or both of them descend from a common origin (Rousseau, 1781/1993) These viewpoints bolster the notion that music and language, both of which involve complex and meaningful sound sequences (Patel, 2008), are reciprocally connected. The numerals following the syllables stand for the transcribed tones, depicting the relative pitch value within a five-point scale of the talker’s normal frequency range (Chao, 1947). These four tones can be annotated with respective pitch patterns as Tone 1 (T1), level; Tone 2 (T2), rising; Tone 3 (T3), falling-rising; and Tone 4 (T4), falling (Wang et al, 2017)
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