Auditory Cortical Changes Precede Brainstem Changes During Rapid Implicit Learning: Evidence From Human EEG

Short- and long-term neuroplasticity interact during the perceptual learning of concurrent speech

Plasticity from auditory experience shapes the brain's encoding and perception of sound. However, whether such long-term plasticity alters the trajectory of short-term plasticity during speech processing has yet to be investigated. Here, we explored the neural mechanisms and interplay between short- and long-term neuroplasticity for rapid auditory perceptual learning of concurrent speech sounds in young, normal-hearing musicians and nonmusicians. Participants learned to identify double-vowel mixtures during ~ 45 min training sessions recorded simultaneously with high-density electroencephalography (EEG). We analyzed frequency-following responses (FFRs) and event-related potentials (ERPs) to investigate neural correlates of learning at subcortical and cortical levels, respectively. Although both groups showed rapid perceptual learning, musicians showed faster behavioral decisions than nonmusicians overall. Learning-related changes were not apparent in brainstem FFRs. However, plasticity was highly evident in cortex, where ERPs revealed unique hemispheric asymmetries between groups suggestive of different neural strategies (musicians: right hemisphere bias; nonmusicians: left hemisphere). Source reconstruction and the early (150-200 ms) time course of these effects localized learning-induced cortical plasticity to auditory-sensory brain areas. Our findings reinforce the domain-general benefits of musicianship but reveal that successful speech sound learning is driven by a critical interplay between long- and short-term mechanisms of auditory plasticity, which first emerge at a cortical level.

Short- and long-term experience-dependent neuroplasticity interact during the perceptual learning of concurrent speech

Plasticity from auditory experiences shapes brain encoding and perception of sound. However, whether such long-term plasticity alters the trajectory of short-term plasticity during speech processing has yet to be investigated. Here, we explored the neural mechanisms and interplay between short- and long-term neuroplasticity for rapid auditory perceptual learning of concurrent speech sounds in young, normal-hearing musicians and nonmusicians. Participants learned to identify double-vowel mixtures during ∼45 minute training sessions recorded simultaneously with high-density EEG. We analyzed frequency-following responses (FFRs) and event-related potentials (ERPs) to investigate neural correlates of learning at subcortical and cortical levels, respectively. While both groups showed rapid perceptual learning, musicians showed faster behavioral decisions than nonmusicians overall. Learning-related changes were not apparent in brainstem FFRs. However, plasticity was highly evident in cortex, where ERPs revealed unique hemispheric asymmetries between groups suggestive of different neural strategies (musicians: right hemisphere bias; nonmusicians: left hemisphere). Source reconstruction and the early (150-200 ms) time course of these effects localized learning-induced cortical plasticity to auditory-sensory brain areas. Our findings confirm domain-general benefits for musicianship but reveal successful speech sound learning is driven by a critical interplay between long- and short-term mechanisms of auditory plasticity that first emerge at a cortical level.

Children with autism spectrum disorder who demonstrate normal language scores use a bottom-up semantic processing strategy: Evidence from N400 recordings

INTRODUCTION

The N400 is an electrophysiological component that reflects lexical access and integration of words with mental representations.

METHODS

Thirty-five young children with a range of language capabilities (n = 21 neurotypical controls, 10 males, mean age = 6.3 ± 0.9 years; n = 14 children with autism, 12 males, mean age = 6.4 ± 1.1 years) completed an auditory semantic categorization paradigm to evoke the N400. Electroencephalograph (EEG) data were acquired with a 64-channel electrode cap as children listened via ear inserts to binaurally presented single syllable words and decided whether the words were congruent (in) or incongruent (out) with a pre-specified category. EEG data were filtered, epoched, and averaged referenced, and global field power (GFP) was computed. The amplitude of the N400 peak in the GFP was submitted to a multiple linear regression analysis.

RESULTS

N400 amplitude was found to predict language scores only for the children with ASD who have language scores in the normal range (r2  = 0.72).

CONCLUSIONS

This finding that N400 amplitude only predicted language scores in children with ASD and normal language scores suggests that these children may rely more on basic semantic processing (as reflected by the N400) and less on anticipating and predicting upcoming words. This suggests preferential utilization of a bottom-up strategy to access higher order language.

Evaluating normalization accounts against the dense vowel space of Central Swedish

Talkers vary in the phonetic realization of their vowels. One influential hypothesis holds that listeners overcome this inter-talker variability through pre-linguistic auditory mechanisms that normalize the acoustic or phonetic cues that form the input to speech recognition. Dozens of competing normalization accounts exist-including both accounts specific to vowel perception and general purpose accounts that can be applied to any type of cue. We add to the cross-linguistic literature on this matter by comparing normalization accounts against a new phonetically annotated vowel database of Swedish, a language with a particularly dense vowel inventory of 21 vowels differing in quality and quantity. We evaluate normalization accounts on how they differ in predicted consequences for perception. The results indicate that the best performing accounts either center or standardize formants by talker. The study also suggests that general purpose accounts perform as well as vowel-specific accounts, and that vowel normalization operates in both temporal and spectral domains.