Dataset Information

Infants' detection and discrimination of sounds in modulated maskers.

ABSTRACT: Adults and 7-month-old infants were compared in detection and discrimination of sounds in modulated maskers. In two experiments, the level of a target sound was varied to equate listeners' performance in unmodulated noise, and performance was assessed at that level in a noise modulated with the envelope of single-talker speech. While adults' vowel discrimination and tone detection were better in the modulated than in the unmodulated masker, infants' vowel discrimination was poorer in the modulated than in the unmodulated masker. Infants' tone detection was the same in the two maskers. In two additional experiments, each age group was tested at one level with order of testing in modulated and unmodulated maskers counterbalanced across subjects. Both infants and adults discriminated between vowels better in single-talker modulated and sinusoidally amplitude modulated (SAM) maskers than in an unmodulated masker, but infants' modulated-unmodulated difference was smaller than than that of adults. Increasing the modulation depth of the SAM masker did not affect the size of infants' modulated-unmodulated difference. However, infants' asymptotic performance in a modulated masker limits the extent to which their performance could improve. Infants can make use of information in masker dips, but masker modulation may also interfere with their ability to process the target.

SUBMITTER: Werner LA

PROVIDER: S-EPMC3689834 | biostudies-other | 2013 Jun

REPOSITORIES: biostudies-other

ACCESS DATA

Similar Datasets

Project description:At around 7 months of age, human infants begin to reliably produce well-formed syllables containing both consonants and vowels, a behavior called canonical babbling. Over subsequent months, the frequency of canonical babbling continues to increase. How the infant's nervous system supports the acquisition of this ability is unknown. Here we present a computational model that combines a spiking neural network, reinforcement-modulated spike-timing-dependent plasticity, and a human-like vocal tract to simulate the acquisition of canonical babbling. Like human infants, the model's frequency of canonical babbling gradually increases. The model is rewarded when it produces a sound that is more auditorily salient than sounds it has previously produced. This is consistent with data from human infants indicating that contingent adult responses shape infant behavior and with data from deaf and tracheostomized infants indicating that hearing, including hearing one's own vocalizations, is critical for canonical babbling development. Reward receipt increases the level of dopamine in the neural network. The neural network contains a reservoir with recurrent connections and two motor neuron groups, one agonist and one antagonist, which control the masseter and orbicularis oris muscles, promoting or inhibiting mouth closure. The model learns to increase the number of salient, syllabic sounds it produces by adjusting the base level of muscle activation and increasing their range of activity. Our results support the possibility that through dopamine-modulated spike-timing-dependent plasticity, the motor cortex learns to harness its natural oscillations in activity in order to produce syllabic sounds. It thus suggests that learning to produce rhythmic mouth movements for speech production may be supported by general cortical learning mechanisms. The model makes several testable predictions and has implications for our understanding not only of how syllabic vocalizations develop in infancy but also for our understanding of how they may have evolved.

Dataset Information

Infants' detection and discrimination of sounds in modulated maskers.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets