This study investigated adult listeners’ ability to detect age-related cues in child-directed speech (CDS). These findings suggest that in addition to conventional techniques based on mean amplitude analysis and general linear modelling of fNIRS data, the use of MFDF analysis offers a powerful alternative methodology to gain a deeper understanding of long-term memory retrieval in language memory processing. Our results showed that high complexity tasks induced a significantly larger multifractal spectral width in the posterior medial temporal gyri bilaterally, due to higher cognitive demands. Nine Japanese college students participated in a long-term memory retrieval experiment using low (n ± 1) and high (n ± 2) complexity tasks. This study employed multifractal detrended fluctuation (MFDF) analysis focusing on the width of the multifractal spectrum to elucidate whether high complexity tasks increase the fractal dynamics of brain activation signals compared to low complexity tasks. However, it remains unclear whether variability analysis of brain signals obtained using functional near-infrared spectroscopy (fNIRS) is able to separate language-related task conditions. The retrieval of phonological, lexical, semantic, or syntactic language information from long-term memory plays an important role in language processing. Implications for phonological theory are discussed. These results support a similarity-based approach to generalization, particularly one that takes into account articulatorily-based features and natural classes. Participants in both Place and Voice conditions were successful at learning and generalizing the spirantization pattern to novel segments, but rates of generalization were higher in the Voice conditions.

Two groups of participants were trained on items based on voicing (e.g., the Voiced condition was trained on /b/ ➔, and /d/ ➔, and tested on /p/ ➔, and /t/ ➔ ), and two groups of participants were trained on items based on place of articulation (e.g., the Labial condition was trained on /b/ ➔, and /p/ ➔ and tested on /t/ ➔, and /d/ ➔ ). Participants were trained on spirantization for two of four possible stop-fricative pairs, and were tested on their generalization to the held-out segments. Adult, English-speaking learners were exposed to a spirantization pattern in which a stop became a fricative between two vowels (e.g., /bib/ + /o/ ➔ ). The present study makes use of an artificial language learning experiment to explore when and how learners extend a novel phonological pattern to novel segments. In traditional, generative phonology, sound patterns are represented in terms of abstract features, typically based on the articulatory properties of the sounds.

Psyscope language