Are Faster Participants Always Faster? Assessing Reliability of Participants’ Mean Response Speed in Picture Naming

Studies of language production often make use of picture naming tasks to investigate the cognitive processes involved in speaking, and many of these studies report a wide range of individual variability in how long speakers need to prepare the name of a picture. It has been assumed that this variability can be linked to inter-individual differences in cognitive skills or abilities (e.g., attention or working memory); therefore, several studies have tried to explain variability in language production tasks by correlating production measures with scores on cognitive tests. This approach, however, relies on the assumption that participants are reliable over time in their picture naming speed (i.e., that faster speakers are consistently fast). The current study explicitly tested this assumption by asking participants to complete a simple picture naming task twice with one to two weeks in between sessions. In one experiment, we show that picture naming speed has excellent within-task reliability and good test-retest reliability, at least when participants perform the same task in both sessions. In a second experiment with slight task variations across sessions (a speeded and non-speeded picture naming task), we replicated the high split-half reliability and found moderate consistency over tasks. These findings are as predicted under the assumption that the speed of initiating responses for speech production is an intrinsic property or capacity of an individual. We additionally discuss the consequences of these results for the statistical power of correlational designs

Brain-behavior relationships in incidental learning of non-native phonetic categories

Available online 12 September 2019.Research has implicated the left inferior frontal gyrus (LIFG) in mapping acoustic-phonetic input to sound category representations, both in native speech perception and non-native phonetic category learning. At issue is whether this sensitivity reflects access to phonetic category information per se or to explicit category labels, the latter often being required by experimental procedures. The current study employed an incidental learning paradigm designed to increase sensitivity to a difficult non-native phonetic contrast without inducing explicit awareness of the categorical nature of the stimuli. Functional MRI scans revealed frontal sensitivity to phonetic category structure both before and after learning. Additionally, individuals who succeeded most on the learning task showed the largest increases in frontal recruitment after learning. Overall, results suggest that processing novel phonetic category information entails a reliance on frontal brain regions, even in the absence of explicit category labels.This research was supported by NIH grant R01 DC013064 to EBM and NIH NIDCD Grant R01 DC006220 to SEB. The authors thank F. Sayako Earle for assistance with stimulus development; members of the Language and Brain lab for help with data collection and their feedback throughout the project; Elisa Medeiros for assistance with collection of fMRI data; Paul Taylor for assistance with neuroimaging analyses; and attendees of the 2016 Meeting of the Psychonomic Society and the 2017 Meeting of the Society for Neurobiology of Language for helpful feedback on this project. We also extend thanks to two anonymous reviewers for helpful feedback on a previous version of this manuscript

Neural Correlates of Native-language Speech Perception and Non-native Speech Sound Learning

Many studies of non-native speech sound learning report a great deal of individual variability; some learners master the sounds of a second language with ease, while others struggle to perceive and produce sounds, even after years of learning the language. Although some contributions of phonological, auditory, or cognitive skills have been found to predict non-native speech sound learning ability as measured by laboratory tasks, the field lacks a comprehensive understanding of where these differences originate from. Recent findings, however, suggest that individual differences in sleep duration may predict learning after a period of offline consolidation, though these findings are mixed. Another issue is that the large amount of individual variability seen in studies of non-native learning makes it difficult to obtain precise estimates of effect sizes. Therefore, the first aim of this dissertation was to replicate and extend recent behavioral and neuroimaging findings in non-native speech sound learning with a larger sample size than is typical. The second goal was to test a new question, namely, that how consistently and categorically listeners perceive native-language sounds will predict success on non-native speech sound learning tasks. Finally, we sought to establish whether measures of brain structure can predict how categorically listeners perceive sounds in the native language and how consistently they respond to those sounds. We did not replicate recent findings showing behavioral improvement after sleep on non-native speech sound learning tasks, nor did we replicate the finding that sleep duration predicts overnight improvement. However, gyrification of the bilateral transverse temporal gyri and hippocampal volume predicted an individual’s overnight improvement, suggesting a role for memory consolidation, even though we did not see overnight improvement at the group level. We additionally did not find that individual differences in categorical perception predicted non-native speech sound learning, which presents a challenge for some predominant theories of non-native speech sound learning, which future research will have to address. Overall, learners with reduced surface area and volume in frontal regions showed more graded and consistent perception of native-language speech sounds, supporting the notion that these regions underlie categorical perception