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Purpose: If language production is impaired, will gestures compensate? Evidence in favor of this prediction has often been argued to come from aphasia, but it remains contested. Here, we tested whether thought content not present in speech due to language impairment is manifested in gestures, in 20 people with dysfluent (Broca's) aphasia, 20 people with fluent (Wernicke's) aphasia, and 20 matched neurotypical controls. Method: A new annotation scheme was created distinguishing types of gestures and whether they co-occurred with fluent or dysfluent/absent speech and were temporally aligned in content with coproduced speech. Results: Across both aphasia types, noncontent (beat) gestures, which by their nature cannot compensate for lost speech content, constituted the greatest proportion of all types of gestures produced. Content (i.e., descriptive, referential, and metaphorical) gestures were largely coproduced with fluent rather than dysfluent speech and tended to be aligned with the content conveyed in speech. They also did not differ in quantity depending on whether the dysfluencies were eventually resolved or not. Neither aphasia severity nor comprehension ability had an impact on the total amount of content gesture produced in people with aphasia, which was instead positively correlated with speech fluency. Conclusions: Together, these results suggest that gestures are unlikely to have a role in compensating for linguistic deficits and to serve as a representational system conveying thought content independent of language. Surprisingly, aphasia rather is a model of how gesture and language are inherently integrated and aligned: Even when language is impaired, it remains the essential provider of content.

Purpose: If language production is impaired, will gestures compensate? Evidence in favor of this prediction has often been argued to come from aphasia, but it remains contested. Here, we tested whether thought content not present in speech due to language impairment is manifested in gestures, in 20 people with dysfluent (Broca's) aphasia, 20 people with fluent (Wernicke's) aphasia, and 20 matched neurotypical controls. Method: A new annotation scheme was created distinguishing types of gestures and whether they co-occurred with fluent or dysfluent/absent speech and were temporally aligned in content with coproduced speech. Results: Across both aphasia types, noncontent (beat) gestures, which by their nature cannot compensate for lost speech content, constituted the greatest proportion of all types of gestures produced. Content (i.e., descriptive, referential, and metaphorical) gestures were largely coproduced with fluent rather than dysfluent speech and tended to be aligned with the content conveyed in speech. They also did not differ in quantity depending on whether the dysfluencies were eventually resolved or not. Neither aphasia severity nor comprehension ability had an impact on the total amount of content gesture produced in people with aphasia, which was instead positively correlated with speech fluency. Conclusions: Together, these results suggest that gestures are unlikely to have a role in compensating for linguistic deficits and to serve as a representational system conveying thought content independent of language. Surprisingly, aphasia rather is a model of how gesture and language are inherently integrated and aligned: Even when language is impaired, it remains the essential provider of content., When communicating, people naturally use gestures for expressing ideas, intentions, or personal and emotional feelings (Knapp & Hall, 1997). McNeill (1992) defines gesture as arm and hand movements that synchronize [...]

Background & aims: Individuals with non- or minimally verbal autism (nvASD) are primarily characterized by a severe speech production deficit, with speech limited to no or only a few words by school age. Significant unclarity remains over variability in language profiles across the lifespan, the nature of the language impairment seen, and (dis-) associations between linguistic and nonverbal cognitive measures. Methods: To address these questions, we recruited both a school-age and an adult group with nvASD (total N = 49) and investigated relations between expressive and receptive language, and between these and nonverbal intelligence quotient (NVIQ) and sense-making capacities (the ComFor test). Results: Results revealed limited variation across this sample in receptive language, which in turn predicted expressive language levels. Importantly, an upward trend in verbal mental age (VMA) across increasing chronological age was seen in the youngsters (only). A radical dissociation between NVIQ and both expressive and receptive language transpired as well, and a subset of individuals with normal NVIQ were comparable in terms of any other cognitive aspect. Sense-making reached symbolic levels in 62.2% of the sample and loaded on both verbal and nonverbal factors. Conclusions: These patterns inform theories of nvASD by revealing an impairment that is not conceptualizable as one of expressive language only, sharply limits learning opportunities across the lifespan, and cannot be compensated for by nonverbal cognition. Implications: These findings stress the need to seize developmental opportunities that may disappear when youngsters turn into adults, via therapies that specifically target language as a central cognitive system comprising both production and comprehension.

Purpose: Episodic memory decline is a hallmark of Alzheimer's disease (AD) and linked to deficits in episodic thinking directed to the future. We addressed the question whether a deficit in episodic thinking can be picked up directly from connected speech and its detection can be automatized. Method: We linguistically classified 2,809 utterances (including embedded clauses in the utterances) from picture descriptions from 70 healthy older controls, 82 people with mild probable AD (pAD), and 46 people with moderate pAD for whether they were episodic, nonepisodic, or "other" (e.g., off-task). Generalized linear regression models were used to investigate how ratios of these categories change in AD, controlling for age, gender, and education. Finally, we applied deep learning technique to explore the feasibility of automating the episodicity analysis. Results: Decline in episodicity significantly distinguished controls from both mild pAD and moderate pAD. Correlation analysis suggested this decline not to be an effect of age, gender, and education but of cognitive ability. The decline was not compensated by an increase of nonepisodic utterances but mainly of off-task expressions. A transformer-based classifier to explore the possibility of automatizing the classification of episodicity achieved a macro F1 score of 0.913 in the ternary classification. Conclusion: These results show that a loss of episodicity is an early effect in AD that is manifested in spontaneous speech and can be reliably measured by both humans and machines. [ABSTRACT FROM AUTHOR]

Background: Decline in language has emerged as a new potential biomarker for the early detection of Alzheimer's disease (AD). It remains unclear how sensitive language measures are across different tasks, language domains, and languages, and to what extent changes can be reliably detected in early stages such as subjective cognitive decline (SCD) and mild cognitive impairment (MCI). Method: Using a scene construction task for speech elicitation in a new Spanish/Catalan speaking cohort (N = 119), we automatically extracted features across seven domains, three acoustic (spectral, cepstral, and voice quality), one prosodic, and three from text (morpholexical, semantic, and syntactic). They were forwarded to a random forest classifier to evaluate the discriminability of participants with probable AD dementia, amnestic and nonamnestic MCI, SCD, and cognitively healthy controls. Repeated-measures analyses of variance and paired-samples Wilcoxon signed-ranks test were used to assess whether and how performance differs significantly across groups and linguistic domains. Results: The performance scores of the machine learning classifier were generally satisfactorily high, with the highest scores over .9. Model performance was significantly different for linguistic domains (p < .001), and speech versus text (p = .043), with speech features outperforming textual features, and voice quality performing best. High diagnostic classification accuracies were seen even within both cognitively healthy (controls vs. SCD) and MCI (amnestic and nonamnestic) groups. Conclusion: Speech-based machine learning is powerful in detecting cognitive decline and probable AD dementia across a range of different feature domains, though important differences exist between these domains as well. [ABSTRACT FROM AUTHOR]

All forms of nominal reference, whether quantificational, definite, rigid, deictic, or personal, require that the nominals in question appear in relevant grammatical configurations. Reference is in this sense a grammatical phenomenon. It is never determined lexically or a word-world relation in a purely semantic or causal sense. Here it is further argued that the principles of the grammar of object-reference naturally extend to cases where the reference of one nominal depends on that of another, i.e. the grammar of referential dependence, without any further special grammatical relations such as ‘binding’ required. This further includes a relation of (referential) identity.

Much philosophical attention has been devoted to the truth predicates of natural language and their logic. However, lexical truth predicates are neither necessary nor sufficient for a truth-attribution to occur, which warrants closer attention to the grammar of truth attribution. A unified analysis of five constructions is offered here, in two of which the lexical truth predicate occurs (It's true that John left and That John left is true), while in the three remaining, it does not (John left; It seems that John left; and It's that John left). This analysis is philosophically significant for four reasons. First, it explains why speakers of natural language find standard instances of Tarski-inspired equivalences (e.g. That John left is true iff John left) intuitively compelling. Second, it derives the widespread 'deflationist' intuition that truth has no substantive content. Third, insofar as the deflationist sees insights on truth as flowing from understanding our practice of truth attribution, it furthers the deflationist agenda through a new analysis of such attributions. Finally, it advances the philosophical project of the 'naturalization' of truth by reducing our understanding of truth to our competence in the grammar of truth, as an aspect of our biological endowment. [ABSTRACT FROM AUTHOR]

Throughout its long history, the project of a science of grammar has always been an inherently philosophical one, in which the study of grammar was taken to have special epistemological significance. I ask why 20th and 21st century inquiry into Universal Grammar (UG) has largely lost this dimension, a fact that I argue is partially responsible for the prevailing controversy around UG, relating to its formulation, scope, and biological basis. This paper argues for a re-conceptualization of this program along ways that answer these criticisms and are more in line with a pre-modern conception of a science of grammar, bringing out its philosophical significance. Central to the new conception is the role of grammar in giving human thought a species-specific and uniquely linguistic structural format, consistent with the recent claim that UG primarily constrains the Language of Thought, yet different from it in other ways, such as in stressing the role of grammar in establishing a system of deictic reference, which depends on the externalization of grammar in some physical medium. Although UG on the new conception is not the study of linguistic variation but the study of "sapiens"-specific mode of thought, it cannot be dissolved into the study of thought (or semantics) as such: for the mode of thought in question uniquely takes a grammatical format and grammatical meaning is unavailable either pre-linguistically or lexically.

This workshop summary on natural language processing (NLP) markers for psychosis and other psychiatric disorders presents some of the clinical and research issues that NLP markers might address and some of the activities needed to move in that direction. We propose that the optimal development of NLP markers would occur in the context of research efforts to map out the underlying mechanisms of psychosis and other disorders. In this workshop, we identified some of the challenges to be addressed in developing and implementing NLP markers-based Clinical Decision Support Systems (CDSSs) in psychiatric practice, especially with respect to psychosis. Of note, a CDSS is meant to enhance decision-making by clinicians by providing additional relevant information primarily through software (although CDSSs are not without risks). In psychiatry, a field that relies on subjective clinical ratings that condense rich temporal behavioral information, the inclusion of computational quantitative NLP markers can plausibly lead to operationalized decision models in place of idiosyncratic ones, although ethical issues must always be paramount. [ABSTRACT FROM AUTHOR]

Preschoolers naturally form mental representations that capture generic knowledge about object kinds. These have been considered to pose a special explanatory and learning challenge. We here argue for a new deductive model of them, where (i) the representations in question have a linguistic format from the start; (ii) they are inherently structurally simpler compared to reference to individuals or quantifications; and (iii) formed in communicative contexts because communication in humans is linked to language. In this model, specific language‐related resources explain the scope and limits of the forms of knowledge obtained, illustrating how language and cognition develop in tandem. [ABSTRACT FROM AUTHOR]