The uncertainty associated with paradigmatic families has been shown to correlate with their phonetic characteristics in speech, suggesting that representations of complex sublexical relations between words are part of speaker knowledge. To better understand this, recent studies have used two-layer neural network models to examine the way paradigmatic uncertainty emerges in learning. However, to date this work has largely ignored the way choices about the representation of inflectional and grammatical functions (IFS) in models strongly influence what they subsequently learn. To (...) explore the consequences of this, we investigate how representations of IFS in the input-output structures of learning models affect the capacity of uncertainty estimates derived from them to account for phonetic variability in speech. Specifically, we examine whether IFS are best represented as outputs to neural networks (as in previous studies) or as inputs by building models that embody both choices and examining their capacity to account for uncertainty effects in the formant trajectories of word final [ɐ], which in German discriminates around sixty different IFS. Overall, we find that formants are enhanced as the uncertainty associated with IFS decreases. This result dovetails with a growing number of studies of morphological and inflectional families that have shown that enhancement is associated with lower uncertainty in context. Importantly, we also find that in models where IFS serve as inputs—as our theoretical analysis suggests they ought to—its uncertainty measures provide better fits to the empirical variance observed in [ɐ] formants than models where IFS serve as outputs. This supports our suggestion that IFS serve as cognitive cues during speech production, and should be treated as such in modeling. It is also consistent with the idea that when IFS serve as inputs to a learning network. This maintains the distinction between those parts of the network that represent message and those that represent signal. We conclude by describing how maintaining a “signal-message-uncertainty distinction” can allow us to reconcile a range of apparently contradictory findings about the relationship between articulation and uncertainty in context. (shrink)

People undergo many idiosyncratic experiences throughout their lives that may contribute to individual differences in the size and structure of their knowledge representations. Ultimately, these can have important implications for individuals' cognitive performance. We review evidence that suggests a relationship between individual experiences, the size and structure of semantic representations, as well as individual and age differences in cognitive performance. We conclude that the extent to which experience-dependent changes in semantic representations contribute to individual differences in cognitive aging remains unclear. (...) To help fill this gap, we outline an empirical agenda that utilizes network analysis and involves the concurrent assessment of large-scale semantic networks and cognitive performance in younger and older adults. We present preliminary data to establish the feasibility and limitations of such empirical, network-analytical approaches. (shrink)

The lexical–semantic organization of the mental lexicon is bound to change across the lifespan. Nevertheless, the effects of lexical–semantic factors on word processing are usually based on studies enrolling young adult cohorts. The current study aims to investigate to what extent age‐specific semantic organization predicts performance in referential word production over the lifespan, from school‐age children to older adults. In Study 1, we conducted a free semantic association task with participants from six age‐groups (ranging from 10 to 80 years old) (...) to compute measures that capture age‐specific properties of the mental lexicon across the lifespan. These measures relate to lifespan changes in the Available Richness of the mental lexicon and in the lexical–semantic Network Prototypicality of concrete words. In Study 2, we used the collected data to predict performance in a picture‐naming task on a new group of participants within the same age‐groups as for Study 1. The results show that age‐specific semantic Available Richness and Network Prototypicality affect word production speed while the semantic variables collected only in young adults do not. A richer and more prototypical semantic network across subjects from a given age‐group is associated with faster word production speed. The current results indicate that age‐specific semantic organization is crucial to predict lexical–semantic behaviors across the lifespan. Similarly, these results also provide cues to the understanding of the lexical–semantic properties of the mental lexicon and to lexical selection in referential tasks. (shrink)

While cognitive changes in aging and neurodegenerative disease have been widely studied, language changes in these populations are less well understood. Inflecting novel words in a language with complex inflectional paradigms provides a good opportunity to observe how language processes change in normal and abnormal aging. Studies of language acquisition suggest that children inflect novel words based on their phonological similarity to real words they already know. It is unclear whether speakers continue to use the same strategy when encountering novel (...) words throughout the lifespan or whether adult speakers apply symbolic rules. We administered a simple speech elicitation task involving Finnish‐conforming pseudo‐words and real Finnish words to healthy older adults, individuals with mild cognitive impairment, and individuals with Alzheimer's disease (AD) to investigate inflectional choices in these groups and how linguistic variables and disease severity predict inflection patterns. Phonological resemblance of novel words to both a regular and an irregular inflectional type, as well as bigram frequency of the novel words, significantly influenced participants' inflectional choices for novel words among the healthy elderly group and people with AD. The results support theories of inflection by phonological analogy (single‐route models) and contradict theories advocating for formal symbolic rules (dual‐route models). (shrink)

Many models of word recognition assume that processing proceeds sequentially from analysis of form to analysis of meaning. In the context of morphological processing, this implies that morphemes are processed as units of form prior to any influence of their meanings. Some interpret the apparent absence of differences in recognition latencies to targets (SNEAK) in form and semantically similar (sneaky-SNEAK) and in form similar and semantically dissimilar (sneaker-SNEAK) prime contexts at an SOA of 48 ms as consistent with this claim. (...) To determine the time course over which degree of semantic similarity between morphologically structured primes and their targets influences recognition in the forward masked priming variant of the lexical decision paradigm, we compared facilitation for the same targets after semantically similar and dissimilar primes across a range of SOAs. The effect of shared semantics on recognition latency increased linearly with SOA when long SOAs were intermixed (Exp. 1) and latencies were significantly faster after semantically similar than dissimilar primes at homogeneous SOAs of 48 ms (Exp. 2) and 34 ms (Exp. 3). Results limit the scope of form-then-semantics models of recognition and demonstrate that semantics influences even the very early stages of recognition. Finally, once general behavior across trials has been accounted for, we fail to provide evidence for individual differences in morphological processing that can be linked to measures of reading proficiency. (shrink)

Ramscar, Yarlett, Dye, Denny, and Thorpe (2010) showed how, consistent with the predictions of error‐driven learning models, the order in which stimuli are presented in training can affect category learning. Specifically, learners exposed to artificial language input where objects preceded their labels learned the discriminating features of categories better than learners exposed to input where labels preceded objects. We sought to replicate this finding in two online experiments employing the same tests used originally: A four pictures test (match a label (...) to one of four pictures) and a four labels test (match a picture to one of four labels). In our study, only findings from the four pictures test were consistent with the original result. Additionally, the effect sizes observed were smaller, and participants over‐generalized high‐frequency category labels more than in the original study. We suggest that although Ramscar, Yarlett, Dye, Denny, and Thorpe (2010) feature‐label order predictions were derived from error‐driven learning, they failed to consider that this mechanism also predicts that performance in any training paradigm must inevitably be influenced by participant prior experience. We consider our findings in light of these factors, and discuss implications for the generalizability and replication of training studies. (shrink)

Vocabulary size has been suggested as a useful measure of “verbal abilities” that correlates with speech recognition scores. Knowing more words is linked to better speech recognition. How vocabulary knowledge translates to general speech recognition mechanisms, how these mechanisms relate to offline speech recognition scores, and how they may be modulated by acoustical distortion or age, is less clear. Age-related differences in linguistic measures may predict age-related differences in speech recognition in noise performance. We hypothesized that speech recognition performance can (...) be predicted by the efficiency of lexical access, which refers to the speed with which a given word can be searched and accessed relative to the size of the mental lexicon. We tested speech recognition in a clinical German sentence-in-noise test at two signal-to-noise ratios (SNRs), in 22 younger (18–35 years) and 22 older (60–78 years) listeners with normal hearing. We also assessed receptive vocabulary, lexical access time, verbal working memory, and hearing thresholds as measures of individual differences. Age group, SNR level, vocabulary size, and lexical access time were significant predictors of individual speech recognition scores, but working memory and hearing threshold were not. Interestingly, longer accessing times were correlated with better speech recognition scores. Hierarchical regression models for each subset of age group and SNR showed very similar patterns: the combination of vocabulary size and lexical access time contributed most to speech recognition performance; only for the younger group at the better SNR (yielding about 85% correct speech recognition) did vocabulary size alone predict performance. Our data suggest that successful speech recognition in noise is mainly modulated by the efficiency of lexical access. This suggests that older adults’ poorer performance in the speech recognition task may have arisen from reduced efficiency in lexical access; with an average vocabulary size similar to that of younger adults, they were still slower in lexical access. (shrink)

Understanding the changes in our language abilities along the lifespan is a crucial step for understanding the aging process both in normal and in abnormal circumstances. Besides controlled experimental tasks, it is equally crucial to investigate language in unconstrained conversation. I present an information-theoretical analysis of a corpus of dyadic conversations investigating how the richness of the vocabulary, the word-internal structure, and the syntax of the utterances evolves as a function of the speaker's age and sex. Although vocabulary diversity increases (...) throughout the lifetime, grammatical diversities follow a different pattern, which also differs between women and men. Women use increasingly diverse syntactic structures at least up to their late fifties, and they do not deteriorate in terms of fluency through their lifespan. However, from age 45 onward, men exhibit a decrease in the diversity of the syntactic structures they use, coupled with an increased number of speech disfluencies. (shrink)

Previous studies provided evidence for a connection between language processing and language change. We add to these studies with an exploration of the influence of lexical-distributional properties of words in orthographic space, semantic space, and the mapping between orthographic and semantic space on the probability of lexical extinction. Through a binomial linear regression analysis, we investigated the probability of lexical extinction by the first decade of the twenty-first century (2000s) for words that existed in the first decade of the nineteenth-century (...) (1800s) in eight data sets for five languages: English, French, German, Italian, and Spanish. The binomial linear regression analysis revealed that words that are more similar in form to other words are less likely to disappear from a language. By contrast, words that are more similar in meaning to other words are more likely to become extinct. In addition, a more consistent mapping between form and meaning protects a word from lexical extinction. A nonlinear time-to-event analysis furthermore revealed that the position of a word in orthographic and semantic space continues to influence the probability of it disappearing from a language for at least 200 years. Effects of the lexical-distributional properties of words under investigation here have been reported in the language processing literature as well. The results reported here, therefore, fit well with a usage-based approach to language change, which holds that language change is at least to some extent connected to cognitive mechanisms in the human brain. (shrink)

Frequency effects are pervasive in studies of language, with higher frequency words being recognized faster than lower frequency words. However, the exact nature of frequency effects has recently been questioned, with some studies finding that contextual information provides a better fit to lexical decision and naming data than word frequency ( Adelman et al., 2006 ). Recent work has cemented the importance of these results by demonstrating that a measure of the semantic diversity of the contexts that a word occurs (...) in provides a powerful measure to account for variability in word recognition latency ( Johns et al., 2012, 2015 ; Jones et al., 2012 ). The goal of the current study is to extend this measure to examine bilingualism and aging, where multiple theories use frequency of occurrence of linguistic constructs as central to accounting for empirical results ( Gollan et al., 2008 ; Ramscar et al., 2014 ). A lexical decision experiment was conducted with four groups of subjects: younger and older monolinguals and bilinguals. Consistent with past results, a semantic diversity variable accounted for the greatest amount of variance in the latency data. In addition, the pattern of fits of semantic diversity across multiple corpora suggests that bilinguals and older adults are more sensitive to semantic diversity information than younger monolinguals. (shrink)

Previous studies have shown that Chinese speakers and non-Chinese speakers exhibit different patterns of cross-modal congruence for the lexical tones of Mandarin Chinese, depending on which features of the pitch they attend to. But is this pattern of language-specific listening a conscious cultural strategy or an automatic processing effect? If automatic, does it also apply when the same pitch contours no longer sound like speech? Implicit Association Tests (IATs) provide an indirect measure of cross-modal association. In a series of IAT (...) studies, conducted with participants with three kinds of language backgrounds (Chinese-dominant bilinguals, Chinese balanced bilinguals, and English speakers with no Chinese experience) we find language-specific congruence effects for Mandarin lexical tones but not for matched sine-wave stimuli. That is, for linguistic stimuli, non-Chinese speakers show advantages for pitch-height congruence (high-pointy, low-curvy); no congruence effects were found for Chinese speakers. For non-linguistic stimuli, all participant groups showed advantages for pitch-height congruence. The present findings suggest that non-lexical tone congruence (high-pointy, low-curvy) is a basic congruence pattern, and the acquisition of a language with lexical tone can alter this perception. (shrink)

Distributional models of semantics learn word meanings from contextual co‐occurrence patterns across a large sample of natural language. Early models, such as LSA and HAL (Landauer & Dumais, 1997; Lund & Burgess, 1996), counted co‐occurrence events; later models, such as BEAGLE (Jones & Mewhort, 2007), replaced counting co‐occurrences with vector accumulation. All of these models learned from positive information only: Words that occur together within a context become related to each other. A recent class of distributional models, referred to as (...) neural embedding models, are based on a prediction process embedded in the functioning of a neural network: Such models predict words that should surround a target word in a given context (e.g., word2vec; Mikolov, Sutskever, Chen, Corrado, & Dean, 2013). An error signal derived from the prediction is used to update each word's representation via backpropagation. However, another key difference in predictive models is their use of negative information in addition to positive information to develop a semantic representation. The models use negative examples to predict words that should not surround a word in a given context. As before, an error signal derived from the prediction prompts an update of the word's representation, a procedure referred to as negative sampling. Standard uses of word2vec recommend a greater or equal ratio of negative to positive sampling. The use of negative information in developing a representation of semantic information is often thought to be intimately associated with word2vec's prediction process. We assess the role of negative information in developing a semantic representation and show that its power does not reflect the use of a prediction mechanism. Finally, we show how negative information can be efficiently integrated into classic count‐based semantic models using parameter‐free analytical transformations. (shrink)

When listening to degraded speech, such as speech delivered by a cochlear implant, listeners make use of top-down linguistic knowledge to facilitate speech recognition. Lexical knowledge supports speech recognition and enhances the perceived clarity of speech. Yet, the extent to which lexical knowledge can be used to effectively compensate for degraded input may depend on the degree of degradation and the listener’s age. The current study investigated lexical effects in the compensation for speech that was degraded via noise-vocoding in younger (...) and older listeners. In an online experiment, younger and older normal-hearing listeners rated the clarity of noise-vocoded sentences on a scale from 1 to 7. Lexical information was provided by matching text primes and the lexical content of the target utterance. Half of the sentences were preceded by a matching text prime, while half were preceded by a non-matching prime. Each sentence also consisted of three key words of high or low lexical frequency and neighborhood density. Sentences were processed to simulate CI hearing, using an eight-channel noise vocoder with varying filter slopes. Results showed that lexical information impacted the perceived clarity of noise-vocoded speech. Noise-vocoded speech was perceived as clearer when preceded by a matching prime, and when sentences included key words with high lexical frequency and low neighborhood density. However, the strength of the lexical effects depended on the level of degradation. Matching text primes had a greater impact for speech with poorer spectral resolution, but lexical content had a smaller impact for speech with poorer spectral resolution. Finally, lexical information appeared to benefit both younger and older listeners. Findings demonstrate that lexical knowledge can be employed by younger and older listeners in cognitive compensation during the processing of noise-vocoded speech. However, lexical content may not be as reliable when the signal is highly degraded. Clinical implications are that for adult CI users, lexical knowledge might be used to compensate for the degraded speech signal, regardless of age, but some CI users may be hindered by a relatively poor signal. (shrink)

Declarative memory abilities change across adulthood. Semantic memory and autobiographic episodic knowledge can remain stable or even increase from mid- to late adulthood, while episodic memory abilities decline in later adulthood. Although it is well known that prior knowledge influences new learning, it is unclear whether the experiential growth of knowledge and memory traces across the lifespan may drive favorable adaptations in some basic memory processes. We hypothesized that an increased reliance on memory integration may be an adaptive mechanism to (...) handle increased interference from accumulating memory traces and knowledge across adulthood. In turn, this may confer an improved ability for integration, observable in middle-age, before the onset of major aging-related declines. We further tested whether the hypothesized increase would be associated with previously observed reductions in memory discrimination performance in midlife. Data from a sample of healthy middle-aged and younger adults did not support the hypothesis of improved integration, as assessed by an associative inference paradigm. Instead, age-equivalent performance on both integration and discrimination measures were observed [Bayes factors 10 = 0.19–0.25], along with expected higher verbal knowledge and slower perceptual speed for middle-aged [10 = 8.52–73.52]. The results contribute to an increased understanding of memory processing in midlife, an understudied portion of the lifespan, and suggest that two core episodic memory processes, integration and discrimination, can be maintained in healthy middle-aged adults. (shrink)

As people age, there is a natural decline in cognitive functioning and brain structure. However, the relationship between brain function and cognition in older adults is neither straightforward nor uniform. Instead, it is complex, influenced by multiple factors, and can vary considerably from one person to another. Reserve, compensation, and maintenance mechanisms may help explain why some older adults can maintain high levels of performance while others struggle. These mechanisms are often studied concerning memory and executive functions that are particularly (...) sensitive to the effects of aging. However, language abilities can also be affected by age, with changes in production fluency. The impact of brain changes on language abilities needs to be further investigated to understand the dynamics and patterns of aging, especially successful aging. We previously modeled several compensatory profiles of language production and lexical access/retrieval in aging within the Lexical Access and Retrieval in Aging (LARA) model. In the present paper, we propose an extended version of the LARA model, called LARA-Connectivity (LARA-C), incorporating recent evidence on brain connectivity. Finally, we discuss factors that may influence the strategies implemented with aging. The LARA-C model can serve as a framework to understand individual performance and open avenues for possible personalized interventions. (shrink)