Han-Gyol Yi

A neural basis of speech-in-noise perception in older adults.

Objective: We investigated a neural basis of speech-in-noise perception in older adults. Hearing loss, the third most common chronic condition in older adults, is most often manifested by difficulty understanding speech in background noise. This trouble with understanding speech in noise, which occurs even in individuals who have normal-hearing thresholds, may arise, in part, from age-related declines in central auditory processing of the temporal and spectral components of speech. We hypothesized that older adults with poorer speech-in-noise (SIN) perception demonstrate impairments in the subcortical representation of speech. Design: In all participants (28 adults, age 60-73 yr), average hearing thresholds calculated from 500 to 4000 Hz were ≤25 dB HL. The participants were evaluated behaviorally with the Hearing in Noise Test (HINT) and neurophysiologically using speech-evoked auditory brainstem responses recorded in quiet and in background noise. The participants were divided based on their HINT scores into top and bottom performing groups that were matched for audiometric thresholds and intelligent quotient. We compared brainstem responses in the two groups, specifically, the average spectral magnitudes of the neural response and the degree to which background noise affected response morphology. Results: In the quiet condition, the bottom SIN group had reduced neural representation of the fundamental frequency of the speech stimulus and an overall reduction in response magnitude. In the noise condition, the bottom SIN group demonstrated greater disruption in noise, reflecting reduction in neural synchrony. The role of brainstem timing is particularly evident in the strong relationship between SIN perception and quiet-to-noise response correlations. All physiologic measures correlated with SIN perception. Conclusion: Adults in the bottom SIN group differed from the audiometrically matched top SIN group in how speech was neurally encoded. The strength of subcortical encoding of the fundamental frequency appears to be a factor in successful speech-in-noise perception in older adults. Given the limitations of amplification, our results suggest the need for inclusion of auditory training to strengthen central auditory processing in older adults with SIN perception difficulties.

Subcortical representation of speech fine structure relates to reading ability.

Impaired perception of consonants by poor readers is reflected in poor subcortical encoding of speech timing and harmonics. We assessed auditory brainstem representation of higher harmonics within a consonant-vowel formant transition to identify relationships between speech fine structure and reading. Responses were analyzed in three ways: a single stimulus polarity, adding responses to inverted polarities (emphasizing low harmonics), and subtracting responses to inverted polarities (emphasizing high harmonics). Poor readers had a reduced representation of higher speech harmonics for subtracted polarities and a single polarity. No group differences were found for the fundamental frequency. These findings strengthen the evidence of subcortical encoding deficits in poor readers for speech fine structure and delineate effective strategies for capturing these neural impairments in humans.

Dual-learning systems during speech category learning

Dual-system models of visual category learning posit the existence of an explicit, hypothesis-testing reflective system, as well as an implicit, procedural-based reflexive system. The reflective and reflexive learning systems are competitive and neurally dissociable. Relatively little is known about the role of these domain-general learning systems in speech category learning. Given the multidimensional, redundant, and variable nature of acoustic cues in speech categories, our working hypothesis is that speech categories are learned reflexively. To this end, we examined the relative contribution of these learning systems to speech learning in adults. Native English speakers learned to categorize Mandarin tone categories over 480 trials. The training protocol involved trial-by-trial feedback and multiple talkers. Experiments 1 and 2 examined the effect of manipulating the timing (immediate vs. delayed) and information content (full vs. minimal) of feedback. Dual-system models of visual category learning predict that delayed feedback and providing rich, informational feedback enhance reflective learning, while immediate and minimally informative feedback enhance reflexive learning. Across the two experiments, our results show that feedback manipulations that targeted reflexive learning enhanced category learning success. In Experiment 3, we examined the role of trial-to-trial talker information (mixed vs. blocked presentation) on speech category learning success. We hypothesized that the mixed condition would enhance reflexive learning by not allowing an association between talker-related acoustic cues and speech categories. Our results show that the mixed talker condition led to relatively greater accuracies. Our experiments demonstrate that speech categories are optimally learned by training methods that target the reflexive learning system.

The Role of Corticostriatal Systems in Speech Category Learning

One of the most difficult category learning problems for humans is learning nonnative speech categories. While feedback-based category training can enhance speech learning, the mechanisms underlying these benefits are unclear. In this functional magnetic resonance imaging study, we investigated neural and computational mechanisms underlying feedback-dependent speech category learning in adults. Positive feedback activated a large corticostriatal network including the dorsolateral prefrontal cortex, inferior parietal lobule, middle temporal gyrus, caudate, putamen, and the ventral striatum. Successful learning was contingent upon the activity of domain-general category learning systems: the fast-learning reflective system, involving the dorsolateral prefrontal cortex that develops and tests explicit rules based on the feedback content, and the slow-learning reflexive system, involving the putamen in which the stimuli are implicitly associated with category responses based on the reward value in feedback. Computational modeling of response strategies revealed significant use of reflective strategies early in training and greater use of reflexive strategies later in training. Reflexive strategy use was associated with increased activation in the putamen. Our results demonstrate a critical role for the reflexive corticostriatal learning system as a function of response strategy and proficiency during speech category learning.

Cortical‐evoked potentials reflect speech‐in‐noise perception in children

Children are known to be particularly vulnerable to the effects of noise on speech perception, and it is commonly acknowledged that failure of central auditory processes can lead to these difficulties with speech‐in‐noise (SIN) perception. However, little is known about the mechanistic relationship between central processes and the perception of SIN. Our aims were twofold: to examine the effects of noise on the central encoding of speech through measurement of cortical event‐related potentials and to examine the relationship between cortical processing and behavioral indices of SIN perception. We recorded cortical responses to the speech syllable [da] in quiet and multi‐talker babble noise in 32 children with a broad range of SIN perception. Outcomes suggest inordinate effects of noise on auditory function in the bottom SIN perceivers compared with the top perceivers. The cortical amplitudes in the top SIN group remained stable between conditions, whereas amplitudes increased significantly in the bottom SIN group, suggesting a developmental central processing impairment in the bottom perceivers that may contribute to difficulties in encoding and perceiving speech in challenging listening environments.

Enhanced procedural learning of speech sound categories in a genetic variant of FOXP2.

A mutation of the forkhead box protein P2 (FOXP2) gene is associated with severe deficits in human speech and language acquisition. In rodents, the humanized form of FOXP2 promotes faster switching from declarative to procedural learning strategies when the two learning systems compete. Here, we examined a polymorphism of FOXP2 (rs6980093) in humans (214 adults; 111 females) for associations with non-native speech category learning success. Neurocomputational modeling results showed that individuals with the GG genotype shifted faster to procedural learning strategies, which are optimal for the task. These findings support an adaptive role for the FOXP2 gene in modulating the function of neural learning systems that have a direct bearing on human speech category learning.

Elevated depressive symptoms enhance reflexive but not reflective auditory category learning.

In vision an extensive literature supports the existence of competitive dual-processing systems of category learning that are grounded in neuroscience and are partially-dissociable. The reflective system is prefrontally-mediated and uses working memory and executive attention to develop and test rules for classifying in an explicit fashion. The reflexive system is striatally-mediated and operates by implicitly associating perception with actions that lead to reinforcement. Although categorization is fundamental to auditory processing, little is known about the learning systems that mediate auditory categorization and even less is known about the effects of individual difference in the relative efficiency of the two learning systems. Previous studies have shown that individuals with elevated depressive symptoms show deficits in reflective processing. We exploit this finding to test critical predictions of the dual-learning systems model in audition. Specifically, we examine the extent to which the two systems are dissociable and competitive. We predicted that elevated depressive symptoms would lead to reflective-optimal learning deficits but reflexive-optimal learning advantages. Because natural speech category learning is reflexive in nature, we made the prediction that elevated depressive symptoms would lead to superior speech learning. In support of our predictions, individuals with elevated depressive symptoms showed a deficit in reflective-optimal auditory category learning, but an advantage in reflexive-optimal auditory category learning. In addition, individuals with elevated depressive symptoms showed an advantage in learning a non-native speech category structure. Computational modeling suggested that the elevated depressive symptom advantage was due to faster, more accurate, and more frequent use of reflexive category learning strategies in individuals with elevated depressive symptoms. The implications of this work for dual-process approach to auditory learning and depression are discussed.

Effect of explicit dimensional instruction on speech category learning.

Learning nonnative speech categories is often considered a challenging task in adulthood. This difficulty is driven by cross-language differences in weighting critical auditory dimensions that differentiate speech categories. For example, previous studies have shown that differentiating Mandarin tonal categories requires attending to dimensions related to pitch height and direction. Relative to native speakers of Mandarin, the pitch direction dimension is underweighted by native English speakers. In the current study, we examined the effect of explicit instructions (dimension instruction) on native English speakers’ Mandarin tone category learning within the framework of a dual-learning systems (DLS) model. This model predicts that successful speech category learning is initially mediated by an explicit, reflective learning system that frequently utilizes unidimensional rules, with an eventual switch to a more implicit, reflexive learning system that utilizes multidimensional rules. Participants were explicitly instructed to focus and/or ignore the pitch height dimension, the pitch direction dimension, or were given no explicit prime. Our results show that instruction instructing participants to focus on pitch direction, and instruction diverting attention away from pitch height, resulted in enhanced tone categorization. Computational modeling of participant responses suggested that instruction related to pitch direction led to faster and more frequent use of multidimensional reflexive strategies and enhanced perceptual selectivity along the previously underweighted pitch direction dimension.

Performance pressure enhances speech learning

Real-world speech learning often occurs in high pressure situations such as trying to communicate in a foreign country. However, the impact of pressure on speech learning success is largely unexplored. In this study, adult, native speakers of English learned non-native speech categories under pressure or no-pressure conditions. In the pressure conditions, participants were informed that they were paired with a (fictitious) partner, and that each had to independently exceed a performance criterion for both to receive a monetary bonus. They were then informed that their partner had exceeded the bonus and the fate of both bonuses depended upon the participants performance. Our results demonstrate that pressure significantly enhanced speech learning success. In addition, neurobiologically-inspired computational modeling revealed that the performance advantage was due to faster and more frequent use of procedural learning strategies. These results integrate two well-studied research domains and suggest a facilitatory role of motivational factors in speech learning performance that may not be captured in traditional training paradigms.

Experience-dependent plasticity in the neural weighting of pitch dimensions: A machine learning approach

We conducted a cross-linguistic study to evaluate the impact of language experience on midbrain encoding of acoustic dimensions. Midbrain electrophysiological responses were recorded to the four Mandarin tones in native Chinese (N = 10) and English (N = 10) listeners, through a counter-balanced block design. English participants were trained over multiple days to achieve tone categorization accuracy and reaction time equal to that of the Chinese participants. We assessed the extent to which the four Mandarin tones could be discerned from the electrophysiological responses, using a data-driven machine learning approach. The machine learning output was used to generate dissimilarity matrices that were subjected to a multidimensional scaling (MDS) model. A two dimensional MDS solution emerged that corresponded to “pitch height” and “pitch direction” of the Mandarin tones. Findings derived from the individual differences scaling (INDSCAL) method revealed that, initially, pitch direction was weighted more by t...