Categorical judgments of otherwise identical phonemes are biased toward hearing words (i.e., “Ganong effect”) suggesting lexical context influences perception of even basic speech primitives. Lexical biasing could manifest via late stage postperceptual mechanisms related to decision or, alternatively, top–down linguistic inference that acts on early perceptual coding. Here, we exploited the temporal sensitivity of EEG to resolve the spatiotemporal dynamics of these context-related influences on speech categorization. Listeners rapidly classified sounds from a /gɪ/-/kɪ/ gradient presented in opposing word–nonword contexts ( GIFT–kift vs. giss–KISS ), designed to bias perception toward lexical items. Phonetic perception shifted toward the direction of words, establishing a robust Ganong effect behaviorally. ERPs revealed a neural analog of lexical biasing emerging within ∼200 msec. Source analyses uncovered a distributed neural network supporting the Ganong including middle temporal gyrus, inferior parietal lobe, and middle frontal cortex. Yet, among Ganong-sensitive regions, only left middle temporal gyrus and inferior parietal lobe predicted behavioral susceptibility to lexical influence. Our findings confirm lexical status rapidly constrains sublexical categorical representations for speech within several hundred milliseconds but likely does so outside the purview of canonical auditory-sensory brain areas.

Musicianship has been associated with auditory processing benefits. It is unclear, however, whether pitch processing experience in nonmusical contexts, namely, speaking a tone language, has comparable associations with auditory processing. Studies comparing the auditory processing of musicians and tone language speakers have shown varying degrees of between-group similarity with regard to perceptual processing benefits and, particularly, nonlinguistic pitch processing. To test whether the auditory abilities honed by musicianship or speaking a tone language differentially impact the neural networks supporting nonlinguistic pitch processing (relative to timbral processing), we employed a novel application of brain signal variability (BSV) analysis. BSV is a metric of information processing capacity and holds great potential for understanding the neural underpinnings of experience-dependent plasticity. Here, we measured BSV in electroencephalograms of musicians, tone language-speaking nonmusicians, and English-speaking nonmusicians (controls) during passive listening of music and speech sound contrasts. Although musicians showed greater BSV across the board, each group showed a unique spatiotemporal distribution in neural network engagement: Controls had greater BSV for speech than music; tone language-speaking nonmusicians showed the opposite effect; musicians showed similar BSV for both domains. Collectively, results suggest that musical and tone language pitch experience differentially affect auditory processing capacity within the cerebral cortex. However, information processing capacity is graded: More experience with pitch is associated with greater BSV when processing this cue. Higher BSV in musicians may suggest increased information integration within the brain networks subserving speech and music, which may be related to their well-documented advantages on a wide variety of speech-related tasks.

Neural encoding of pitch in the auditory brainstem is known to be shaped by long-term experience with language or music, implying that early sensory processing is subject to experience-dependent neural plasticity. In language, pitch patterns consist of sequences of continuous, curvilinear contours; in music, pitch patterns consist of relatively discrete, stair-stepped sequences of notes. The primary aim was to determine the influence of domain-specific experience (language vs. music) on the encoding of pitch in the brainstem. Frequency-following responses were recorded from the brainstem in native Chinese, English amateur musicians, and English nonmusicians in response to iterated rippled noise homologues of a musical pitch interval (major third; M3) and a lexical tone (Mandarin tone 2; T2) from the music and language domains, respectively. Pitch-tracking accuracy (whole contour) and pitch strength (50 msec sections) were computed from the brainstem responses using autocorrelation algorithms. Pitch-tracking accuracy was higher in the Chinese and musicians than in the nonmusicians across domains. Pitch strength was more robust across sections in musicians than in nonmusicians regardless of domain. In contrast, the Chinese showed larger pitch strength, relative to nonmusicians, only in those sections of T2 with rapid changes in pitch. Interestingly, musicians exhibited greater pitch strength than the Chinese in one section of M3, corresponding to the onset of the second musical note, and two sections within T2, corresponding to a note along the diatonic musical scale. We infer that experience-dependent plasticity of brainstem responses is shaped by the relative saliency of acoustic dimensions underlying the pitch patterns associated with a particular domain.