Verbal ability in postmenopausal women in relation to age, cognitive and reproductive factors

Word-finding difficulties have been associated with age and, in women, lowered sex hormone levels following menopause. However, there is limited understanding of the ways that specific aspects of word-finding are shaped by women's age, reproductive histories, and background factors such as education. The current study investigated the effects of age, cognitive and reproductive factors on word-finding abilities in 53 healthy postmenopausal women aged 48-79. A questionnaire was used to gather demographic information and reproductive history. A battery of verbal fluency, continuous series, and naming tasks was designed to assess word-finding across different sensory modalities and cognitive demands. Category and letter fluency were quantified as total number of correct words produced on each task. For continuous series, switch rates and switch costs were computed. For the naming tasks, accuracy and latency measures were used. There were three key findings. Firstly, there was a consistent positive association between education and all word-finding measures, i.e., verbal fluency, continuous series, and naming. Secondly, age-related declines were seen on tasks heavily dependent on working memory such as the continuous series task. Thirdly, reproductive factors across the lifespan such as age at menarche and reproductive years showed subtle effects on naming abilities, but not on verbal fluency or continuous series. The results highlight that word-finding abilities in healthy postmenopausal women are shaped by factors associated with their early years (education, age at menarche) and later adult life (age, reproductive years). The study also distinguished between the more global effects of education, and the more task-specific associations with age and reproductive variables, on verbal task performance after menopause

The crosslinguistic acquisition of sentence structure: Computational modeling and grammaticality judgments from adult and child speakers of English, Japanese, Hindi, Hebrew and K'iche'

This preregistered study tested three theoretical proposals for how children form productive yet restricted linguistic generalizations, avoiding errors such as *The clown laughed the man, across three age groups (5–6 years, 9–10 years, adults) and five languages (English, Japanese, Hindi, Hebrew and K'iche'). Participants rated, on a five-point scale, correct and ungrammatical sentences describing events of causation (e.g., *Someone laughed the man; Someone made the man laugh; Someone broke the truck; ?Someone made the truck break). The verb-semantics hypothesis predicts that, for all languages, by-verb differences in acceptability ratings will be predicted by the extent to which the causing and caused event (e.g., amusing and laughing) merge conceptually into a single event (as rated by separate groups of adult participants). The entrenchment and preemption hypotheses predict, for all languages, that by-verb differences in acceptability ratings will be predicted by, respectively, the verb's relative overall frequency, and frequency in nearly-synonymous constructions (e.g., X made Y laugh for *Someone laughed the man). Analysis using mixed effects models revealed that entrenchment/preemption effects (which could not be distinguished due to collinearity) were observed for all age groups and all languages except K'iche', which suffered from a thin corpus and showed only preemption sporadically. All languages showed effects of event-merge semantics, except K'iche' which showed only effects of supplementary semantic predictors. We end by presenting a computational model which successfully simulates this pattern of results in a single discriminative-learning mechanism, achieving by-verb correlations of around r = 0.75 with human judgment data.Additional co-authors: Rukmini Bhaya Nair, Seth Campbell, Clifton Pye, Pedro Mateo Pedro, Sindy Fabiola Can Pixabaj, Mario Marroquín Pelíz, Margarita Julajuj Mendoz

Testing a computational model of causative overgeneralizations: Child judgment and production data from English, Hebrew, Hindi, Japanese and K'iche'.

How do language learners avoid the production of verb argument structure overgeneralization errors ( *The clown laughed the man c.f. The clown made the man laugh), while retaining the ability to apply such generalizations productively when appropriate? This question has long been seen as one that is both particularly central to acquisition research and particularly challenging. Focussing on causative overgeneralization errors of this type, a previous study reported a computational model that learns, on the basis of corpus data and human-derived verb-semantic-feature ratings, to predict adults' by-verb preferences for less- versus more-transparent causative forms (e.g., * The clown laughed the man vs The clown made the man laugh) across English, Hebrew, Hindi, Japanese and K'iche Mayan. Here, we tested the ability of this model (and an expanded version with multiple hidden layers) to explain binary grammaticality judgment data from children aged 4;0-5;0, and elicited-production data from children aged 4;0-5;0 and 5;6-6;6 ( N=48 per language). In general, the model successfully simulated both children's judgment and production data, with correlations of r=0.5-0.6 and r=0.75-0.85, respectively, and also generalized to unseen verbs. Importantly, learners of all five languages showed some evidence of making the types of overgeneralization errors - in both judgments and production - previously observed in naturalistic studies of English (e.g., *I'm dancing it). Together with previous findings, the present study demonstrates that a simple learning model can explain (a) adults' continuous judgment data, (b) children's binary judgment data and (c) children's production data (with no training of these datasets), and therefore constitutes a plausible mechanistic account of the acquisition of verbs' argument structure restrictions

Verbal ability in postmenopausal women in relation to age, cognitive and reproductive factors

Word-finding difficulties have been associated with age and, in women, lowered sex hormone levels following menopause. However, there is limited understanding of the ways that specific aspects of word-finding are shaped by women's age, reproductive histories, and background factors such as education. The current study investigated the effects of age, cognitive and reproductive factors on word-finding abilities in 53 healthy postmenopausal women aged 48–79. A questionnaire was used to gather demographic information and reproductive history. A battery of verbal fluency, continuous series, and naming tasks was designed to assess word-finding across different sensory modalities and cognitive demands. Category and letter fluency were quantified as total number of correct words produced on each task. For continuous series, switch rates and switch costs were computed. For the naming tasks, accuracy and latency measures were used. There were three key findings. Firstly, there was a consistent positive association between education and all word-finding measures, i.e., verbal fluency, continuous series, and naming. Secondly, age-related declines were seen on tasks heavily dependent on working memory such as the continuous series task. Thirdly, reproductive factors across the lifespan such as age at menarche and reproductive years showed subtle effects on naming abilities, but not on verbal fluency or continuous series. The results highlight that word-finding abilities in healthy postmenopausal women are shaped by factors associated with their early years (education, age at menarche) and later adult life (age, reproductive years). The study also distinguished between the more global effects of education, and the more task-specific associations with age and reproductive variables, on verbal task performance after menopause

Learners Restrict Their Linguistic Generalizations Using Preemption but Not Entrenchment: Evidence From Artificial-Language-Learning Studies With Adults and Children

A central goal of research into language acquisition is explaining how, when learners generalize to new cases, they appropriately restrict their generalizations (e.g., to avoid producing ungrammatical utterances such as *the clown laughed the man; “*” indicates an ungrammatical form). The past 30 years have seen an unresolved debate between statistical preemption and entrenchment as explanations. Under preemption, the use of a verb in a particular construction (e.g., *the clown laughed the man) is probabilistically blocked by hearing that other verb constructions with similar meanings only (e.g., the clown made the man laugh). Under entrenchment, such errors (e.g., *the clown laughed the man) are probabilistically blocked by hearing any utterance that includes the relevant verb (e.g., by the clown made the man laugh and the man laughed). Across five artificial-language-learning studies, we designed a training regime such that learners received evidence for the (by the relevant hypothesis) ungrammaticality of a particular unattested verb/noun + particle combination (e.g., *chila + kem; *squeako + kem) via either preemption only or entrenchment only. Across all five studies, participants in the preemption condition (as per our preregistered prediction) rated unattested verb/noun + particle combinations as less acceptable for restricted verbs/nouns, which appeared during training, than for unrestricted, novel-at-test verbs/nouns, which did not appear during training, that is, strong evidence for preemption. Participants in the entrenchment condition showed no evidence for such an effect (and in 3/5 experiments, positive evidence for the null). We conclude that a successful model of learning linguistic restrictions must instantiate competition between different forms only where they express the same (or similar) meanings

Children learn ergative case marking in Hindi using statistical preemption and clause-level semantics (intentionality): evidence from acceptability judgment and elicited production studies with children and adults [version 2; peer review: 1 approved, 2 approved with reservations]

Background: A question that lies at the very heart of language acquisition research is how children learn semi-regular systems with exceptions (e.g., the English plural rule that yields cats, dogs, etc, with exceptions feet and men). We investigated this question for Hindi ergative ne marking; another semi-regular but exception-filled system. Generally, in the past tense, the subject of two-participant transitive verbs (e.g., Ram broke the cup) is marked with ne, but there are exceptions. How, then, do children learn when ne marking is required, when it is optional, and when it is ungrammatical? Methods: We conducted two studies using (a) acceptability judgment and (b) elicited production methods with children (aged 4-5, 5-6 and 9-10 years) and adults. Results: All age groups showed effects of statistical preemption: the greater the frequency with which a particular verb appears with versus without ne marking on the subject – relative to other verbs – the greater the extent to which participants (a) accepted and (b) produced ne over zero-marked subjects. Both children and adults also showed effects of clause-level semantics, showing greater acceptance of ne over zero-marked subjects for intentional than unintentional actions. Some evidence of semantic effects at the level of the verb was observed in the elicited production task for children and the judgment task for adults. Conclusions: participants mainly learn ergative marking on an input-based verb-by-verb basis (i.e., via statistical preemption; verb-level semantics), but are also sensitive to clause-level semantic considerations (i.e., the intentionality of the action). These findings add to a growing body of work which suggests that children learn semi-regular, exception-filled systems using both statistics and semantics

Children learn ergative case marking in Hindi using statistical preemption and clause-level semantics (intentionality):evidence from acceptability judgment and elicited production studies with children and adults

Background: A question that lies at the very heart of language acquisition research is how children learn semi-regular systems with exceptions (e.g., the English plural rule that yields cats, dogs, etc, with exceptions feet and men). We investigated this question for Hindi ergative ne marking; another semi-regular but exception-filled system. Generally, in the past tense, the subject of two-participant transitive verbs (e.g., Ram broke the cup) is marked with ne, but there are exceptions. How, then, do children learn when ne marking is required, when it is optional, and when it is ungrammatical? Methods: We conducted two studies using (a) acceptability judgment and (b) elicited production methods with children (aged 4-5, 5-6 and 9-10 years) and adults. Results: All age groups showed effects of statistical preemption: the greater the frequency with which a particular verb appears with versus without ne marking on the subject – relative to other verbs – the greater the extent to which participants (a) accepted and (b) produced ne over zero-marked subjects. Both children and adults also showed effects of clause-level semantics, showing greater acceptance of ne over zero-marked subjects for intentional than unintentional actions. Some evidence of semantic effects at the level of the verb was observed in the elicited production task for children and the judgment task for adults. Conclusions: participants mainly learn ergative marking on an input-based verb-by-verb basis (i.e., via statistical preemption; verb-level semantics), but are also sensitive to clause-level semantic considerations (i.e., the intentionality of the action). These findings add to a growing body of work which suggests that children learn semi-regular, exception-filled systems using both statistics and semantics