Distinguishable features of spontaneous speech in Alzheimer's clinical syndrome and healthy controls.

There is growing evidence that subtle changes in spontaneous speech may reflect early pathological changes in cognitive function. Recent work has found that lexical-semantic features of spontaneous speech predict cognitive dysfunction in individuals with mild cognitive impairment (MCI). The current study assessed whether Ostrand and Gunstad's (OG) lexical-semantic features extend to predicting cognitive status in a sample of individuals with Alzheimer's clinical syndrome (ACS) and healthy controls. Four additional (New) speech indices shown to be important in language processing research were also explored in this sample to extend prior work. Speech transcripts of the Cookie Theft Task from 81 individuals with ACS (Mage = 72.7 years, SD = 8.80, 70.4% female) and 61 healthy controls (HC) (Mage = 63.9 years, SD = 8.52, 62.3% female) from Dementia Bank were analyzed. Random forest and logistic machine learning techniques examined whether subject-level lexical-semantic features could be used to accurately discriminate those with ACS from HC. Results showed that logistic models with the New lexical-semantic features obtained good classification accuracy (78.4%), but the OG features had wider success across machine learning model types. In terms of sensitivity and specificity, the random forest model trained on the OG features was the most balanced. Findings from the current study suggest that features of spontaneous speech used to predict MCI may also distinguish between individuals with ACS and healthy controls. Future work should evaluate these lexical-semantic features in pre-clinical persons to further explore their potential to assist with early detection through speech analysis.

Lexical Speech Features of Spontaneous Speech in Older Persons With and Without Cognitive Impairment: Reliability Analysis.

Background: Speech analysis data are promising digital biomarkers for the early detection of Alzheimer disease. However, despite its importance, very few studies in this area have examined whether older adults produce spontaneous speech with characteristics that are sufficiently consistent to be used as proxy markers of cognitive status. Objective: This preliminary study seeks to investigate consistency across lexical characteristics of speech in older adults with and without cognitive impairment. Methods: A total of 39 older adults from a larger, ongoing study (age: mean 81.1, SD 5.9 years) were included. Participants completed neuropsychological testing and both picture description tasks and expository tasks to elicit speech. Participants with T-scores of ≤40 on ≥2 cognitive tests were categorized as having mild cognitive impairment (MCI). Speech features were computed automatically by using Python and the Natural Language Toolkit. Results: Reliability indices based on mean correlations for picture description tasks and expository tasks were similar in persons with and without MCI (with r ranging from 0.49 to 0.65 within tasks). Intraindividual variability was generally preserved across lexical speech features. Speech rate and filler rate were the most consistent indices for the cognitively intact group, and speech rate was the most consistent for the MCI group. Conclusions: Our findings suggest that automatically calculated lexical properties of speech are consistent in older adults with varying levels of cognitive impairment. These findings encourage further investigation of the utility of speech analysis and other digital biomarkers for monitoring cognitive status over time.

Contributions of semantic and contextual diversity to the word frequency effect in L2 lexical access.

Word frequency has long been viewed as the best predictor of lexical access. However, recent findings have suggested that other corpus-derived metrics (i.e., contextual diversity, semantic diversity) can better explain the word frequency effect in both native speakers and in proficient bilinguals. However, little is known about the contributions of these variables to second language lexical access, where the word frequency effect is purportedly larger than in native speakers. Results from a lexical-decision task with second language learners and a comparison group of native speakers revealed that both contextual diversity and semantic diversity were just as good, if not better, at explaining variance in lexical decision latencies as word frequency. These findings are broadly consistent with that of monolinguals and proficiency bilinguals. The results also underscore the need for more theoretical and empirical focus on different corpus metrics in modelling lexical access. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

Child first language and adult second language are both tied to general-purpose learning systems.

Do the mechanisms underlying language in fact serve general-purpose functions that preexist this uniquely human capacity? To address this contentious and empirically challenging issue, we systematically tested the predictions of a well-studied neurocognitive theory of language motivated by evolutionary principles. Multiple metaanalyses were performed to examine predicted links between language and two general-purpose learning systems, declarative and procedural memory. The results tied lexical abilities to learning only in declarative memory, while grammar was linked to learning in both systems in both child first language and adult second language, in specific ways. In second language learners, grammar was associated with only declarative memory at lower language experience, but with only procedural memory at higher experience. The findings yielded large effect sizes and held consistently across languages, language families, linguistic structures, and tasks, underscoring their reliability and validity. The results, which met the predicted pattern, provide comprehensive evidence that language is tied to general-purpose systems both in children acquiring their native language and adults learning an additional language. Crucially, if language learning relies on these systems, then our extensive knowledge of the systems from animal and human studies may also apply to this domain, leading to predictions that might be unwarranted in the more circumscribed study of language. Thus, by demonstrating a role for these systems in language, the findings simultaneously lay a foundation for potentially important advances in the study of this critical domain.

Recognition memory for novel syntactic structures.

It is commonly held that recognition memory for the surface syntax of language is not robust, especially when compared with memory for gist (e.g., Potter & Lombardi, 1998; Sachs, 1967). Nevertheless, it has been reported that memory for surface syntax occurs and can be surprisingly robust (e.g., Gurevich, Johnson, & Goldberg, 2011). However, most studies have focused on recognition memory for syntactic structures present in participants' native languages, but little is known about memory for novel (e.g., nonnative) syntactic structures. Adults were exposed under incidental learning conditions to a semiartificial language consisting of English words placed into non-English syntactic structures derived from Persian. They were then given an unexpected recognition memory test. Participants demonstrated clear recognition memory for novel syntactic structures. Overall, the results suggest that memory for surface syntax can be acquired under incidental learning conditions, consistent with previous findings in the implicit learning literature using nonlinguistic stimuli. The results also suggest that basic memory processes like those investigated in the recognition memory literature may be involved in the incidental learning of novel syntactic structures, consistent with some current neurocognitive approaches to language (e.g., Ullman, 2004).