Acoustic-phonetic exaggeration of infant-directed speech (IDS) is well documented, but few studies address whether these features are modified with a child's age. Mandarin-speaking mothers were recorded while addressing an adult and their child at two ages (7-12 months and 5 years) to examine the acoustic-phonetic differences between IDS and child-directed speech (CDS). CDS exhibits an exaggeration pattern resembling that of IDS-expanded vowel space, longer vowels, higher pitch, and greater lexical tone differences-when compared to ADS. Longitudinal analysis demonstrated that the extent of acoustic exaggeration is significantly smaller in CDS than in IDS. Age-related changes in maternal speech provide some support for the hypothesis that mothers adjust their speech directed toward children as a function of the child's language ability.

In order for stimuli to be perceptually discriminable, their representations in the brain must be distinct. Investigating the task of discriminating the syllables /ra/ and /la/, we hypothesized that the more distinct a person's neural representations of those sounds were, the better their behavioral ability to discriminate them would be. Standard neuroimaging approaches are ill-suited to testing this hypothesis as they have problems differentiating between neural representations spatially intermingled within the same brain area. We therefore performed multi-voxel pattern-based analysis of the functional magnetic resonance imaging (fMRI) activity elicited by these syllables, in native speakers of English and Japanese. In right primary auditory cortex, the statistical separability of these fMRI patterns predicted subjects' behavioral ability to tell the sounds apart, not only across groups but also across individuals. This opens up a new approach for identifying neural representations and for quantifying their task suitability.

The purpose of this study was to use mismatch responses (MMRs) to explore the dynamic changes of Mandarin speech perception abilities from early to middle childhood. Twenty preschoolers, 18 school-aged children, and 26 adults participated in this study. Two sets of synthesized speech stimuli varying in Mandarin consonant (alveolo-palatal affricate vs. fricative) and lexical tone features (rising vs. contour tone) were used to examine the developmental course of speech perception abilities. The results indicated that only the adult group demonstrated typical early mismatch negativity (MMN) responses, suggesting that the ability to discriminate specific speech cues in Mandarin consonant and lexical tone is a continuing process in preschool- and school-aged children. Additionally, distinct MMR patterns provided evidence indicating diverse developmental courses to different speech characteristics. By incorporating data from the two speech conditions, we propose using MMR profiles consisting of mismatch negativity (MMN), positive mismatch response (p-MMR), and late discriminative negativity (LDN) as possible brain indices to investigate speech perception development.

A number of studies showed that infants reorganize their perception of speech sounds according to their native language categories during their first year of life. Still, information is lacking about the contribution of basic auditory mechanisms to this process. This study aimed to evaluate when native language experience starts to noticeably affect the perceptual processing of basic acoustic cues [i.e., frequency-modulation (FM) and amplitude-modulation information] known to be crucial for speech perception in adults. The discrimination of a lexical-tone contrast (rising versus low) was assessed in 6- and 10-month-old infants learning either French or Mandarin using a visual habituation paradigm. The lexical tones were presented in two conditions designed to either keep intact or to severely degrade the FM and fine spectral cues needed to accurately perceive voice-pitch trajectory. A third condition was designed to assess the discrimination of the same voice-pitch trajectories using click trains containing only the FM cues related to the fundamental-frequency (F0) in French- and Mandarin-learning 10-month-old infants. Results showed that the younger infants of both language groups and the Mandarin-learning 10-month-olds discriminated the intact lexical-tone contrast while French-learning 10-month-olds failed. However, only the French 10-month-olds discriminated degraded lexical tones when FM, and thus voice-pitch cues were reduced. Moreover, Mandarin-learning 10-month-olds were found to discriminate the pitch trajectories as presented in click trains better than French infants. Altogether, these results reveal that the perceptual reorganization occurring during the first year of life for lexical tones is coupled with changes in the auditory ability to use speech modulation cues.

A key goal of cognitive neuroscience is to find simple and direct connections between brain and behaviour. However, fMRI analysis typically involves choices between many possible options, with each choice potentially biasing any brain–behaviour correlations that emerge. Standard methods of fMRI analysis assess each voxel individually, but then face the problem of selection bias when combining those voxels into a region-of-interest, or ROI. Multivariate pattern-based fMRI analysis methods use classifiers to analyse multiple voxels together, but can also introduce selection bias via data-reduction steps as feature selection of voxels, pre-selecting activated regions, or principal components analysis. We show here that strong brain–behaviour links can be revealed without any voxel selection or data reduction, using just plain linear regression as a classifier applied to the whole brain at once, i.e. treating each entire brain volume as a single multi-voxel pattern. The brain–behaviour correlations emerged despite the fact that the classifier was not provided with any information at all about subjects' behaviour, but instead was given only the neural data and its condition-labels. Surprisingly, more powerful classifiers such as a linear SVM and regularised logistic regression produce very similar results. We discuss some possible reasons why the very simple brain-wide linear regression model is able to find correlations with behaviour that are as strong as those obtained on the one hand from a specific ROI and on the other hand from more complex classifiers. In a manner which is unencumbered by arbitrary choices, our approach offers a method for investigating connections between brain and behaviour which is simple, rigorous and direct.