Infant-directed speech does not always involve exaggerated vowel distinctions: Evidence from Danish.

This study compared the acoustic properties of 26 (100% female, 100% monolingual) Danish caregivers' spontaneous speech addressed to their 11- to 24-month-old infants (infant-directed speech, IDS) and an adult experimenter (adult-directed speech, ADS). The data were collected between 2016 and 2018 in Aarhus, Denmark. Prosodic properties of Danish IDS conformed to cross-linguistic patterns, with a higher pitch, greater pitch variability, and slower articulation rate than ADS. However, an acoustic analysis of vocalic properties revealed that Danish IDS had a reduced or similar vowel space, higher within-vowel variability, raised formants, and lower degree of vowel discriminability compared to ADS. None of the measures, except articulation rate, showed age-related differences. These results push for future research to conduct theory-driven comparisons across languages with distinct phonological systems.

The evolution of early symbolic behavior in Homo sapiens.

How did human symbolic behavior evolve? Dating up to about 100,000 y ago, the engraved ochre and ostrich eggshell fragments from the South African Blombos Cave and Diepkloof Rock Shelter provide a unique window into presumed early symbolic traditions of Homo sapiens and how they evolved over a period of more than 30,000 y. Using the engravings as stimuli, we report five experiments which suggest that the engravings evolved adaptively, becoming better-suited for human perception and cognition. More specifically, they became more salient, memorable, reproducible, and expressive of style and human intent. However, they did not become more discriminable over time between or within the two archeological sites. Our observations provide support for an account of the Blombos and Diepkloof engravings as decorations and as socially transmitted cultural traditions. By contrast, there was no clear indication that they served as denotational symbolic signs. Our findings have broad implications for our understanding of early symbolic communication and cognition in H. sapiens.

Introducing tomsup: Theory of mind simulations using Python.

Theory of mind (ToM) is considered crucial for understanding social-cognitive abilities and impairments. However, verbal theories of the mechanisms underlying ToM are often criticized as under-specified and mutually incompatible. This leads to measures of ToM being unreliable, to the extent that even canonical experimental tasks do not require representation of others' mental states. There have been attempts at making computational models of ToM, but these are not easily available for broad research application. In order to help meet these challenges, we here introduce the Python package tomsup: Theory of mind simulations using Python. The package provides a computational eco-system for investigating and comparing computational models of hypothesized ToM mechanisms and for using them as experimental stimuli. The package notably includes an easy-to-use implementation of the variational recursive Bayesian k-ToM model developed by (Devaine, Hollard, & Daunizeau, 2014b) and of simpler non-recursive decision models, for comparison. We provide a series of tutorials on how to: (i) simulate agents relying on the k-ToM model and on a range of simpler types of mechanisms; (ii) employ those agents to generate online experimental stimuli; (iii) analyze the data generated in such experimental setup, and (iv) specify new custom ToM and heuristic cognitive models.

A generalizable speech emotion recognition model reveals depression and remission.

OBJECTIVE: Affective disorders are associated with atypical voice patterns; however, automated voice analyses suffer from small sample sizes and untested generalizability on external data. We investigated a generalizable approach to aid clinical evaluation of depression and remission from voice using transfer learning: We train machine learning models on easily accessible non-clinical datasets and test them on novel clinical data in a different language. METHODS: A Mixture of Experts machine learning model was trained to infer happy/sad emotional state using three publicly available emotional speech corpora in German and US English. We examined the model's predictive ability to classify the presence of depression on Danish speaking healthy controls (N = 42), patients with first-episode major depressive disorder (MDD) (N = 40), and the subset of the same patients who entered remission (N = 25) based on recorded clinical interviews. The model was evaluated on raw, de-noised, and speaker-diarized data. RESULTS: The model showed separation between healthy controls and depressed patients at the first visit, obtaining an AUC of 0.71. Further, speech from patients in remission was indistinguishable from that of the control group. Model predictions were stable throughout the interview, suggesting that 20-30 s of speech might be enough to accurately screen a patient. Background noise (but not speaker diarization) heavily impacted predictions. CONCLUSION: A generalizable speech emotion recognition model can effectively reveal changes in speaker depressive states before and after remission in patients with MDD. Data collection settings and data cleaning are crucial when considering automated voice analysis for clinical purposes.

Taking others into account: combining directly experienced and indirect information in schizophrenia.

An abnormality in inference, resulting in distorted internal models of the world, has been argued to be a common mechanism underlying the heterogeneous psychopathology in schizophrenia. However, findings have been mixed as to wherein the abnormality lies and have typically failed to find convincing relations to symptoms. The limited and inconsistent findings may have been due to methodological limitations of the experimental design, such as conflating other factors (e.g. comprehension) with the inferential process of interest, and a failure to adequately assess and model the key aspects of the inferential process. Here, we investigated probabilistic inference based on multiple sources of information using a new digital version of the beads task, framed in a social context. Thirty-five patients with schizophrenia or schizoaffective disorder with a wide range of symptoms and 40 matched healthy control subjects performed the task, where they guessed the colour of the next marble drawn from a jar based on a sample from the jar as well as the choices and the expressed confidence of four people, each with their own independent sample (which was hidden from participant view). We relied on theoretically motivated computational models to assess which model best captured the inferential process and investigated whether it could serve as a mechanistic model for both psychotic and negative symptoms. We found that 'circular inference' best described the inference process, where patients over-weighed and overcounted direct experience and under-weighed information from others. Crucially, overcounting of direct experience was uniquely associated with most psychotic and negative symptoms. In addition, patients with worse social cognitive function had more difficulties using others' confidence to inform their choices. This difficulty was related to worse real-world functioning. The findings could not be easily ascribed to differences in working memory, executive function, intelligence or antipsychotic medication. These results suggest hallucinations, delusions and negative symptoms could stem from a common underlying abnormality in inference, where directly experienced information is assigned an unreasonable weight and taken into account multiple times. By this, even unreliable first-hand experiences may gain disproportionate significance. The effect could lead to false perceptions (hallucinations), false beliefs (delusions) and deviant social behaviour (e.g. loss of interest in others, bizarre and inappropriate behaviour). This may be particularly problematic for patients with social cognitive deficits, as they may fail to make use of corrective information from others, ultimately leading to worse social functioning.

A systematic review and Bayesian meta-analysis of the development of turn taking in adult-child vocal interactions.

Fluent conversation requires temporal organization between conversational exchanges. By performing a systematic review and Bayesian multi-level meta-analysis, we map the trajectory of infants' turn-taking abilities over the course of early development (0 to 70 months). We synthesize the evidence from 26 studies (78 estimates from 429 unique infants, of which at least 152 are female) reporting response latencies in infant-adult dyadic interactions. The data were collected between 1975 and 2019, exclusively in North America and Europe. Infants took on average circa 1 s to respond, and the evidence of changes in response over time was inconclusive. Infants' response latencies are related to those of their adult conversational partners: an increase of 1 s in adult response latency (e.g., 400 to 1400 ms) would be related to an increase of over 1 s in infant response latency (from 600 to 1857 ms). These results highlight the dynamic reciprocity involved in the temporal organization of turn-taking. Based on these results, we provide recommendations for future avenues of enquiry: studies should analyze how turn-by-turn exchanges develop on a longitudinal timescale, with rich assessment of infants' linguistic and social development.

A Bayesian meta-analysis of infants' ability to perceive audio-visual congruence for speech.

This paper quantifies the extent to which infants can perceive audio-visual congruence for speech information and assesses whether this ability changes with native language exposure over time. A hierarchical Bayesian robust regression model of 92 separate effect sizes extracted from 24 studies indicates a moderate effect size in a positive direction (0.35, CI [0.21: 0.50]). This result suggests that infants possess a robust ability to detect audio-visual congruence for speech. Moderator analyses, moreover, suggest that infants' audio-visual matching ability for speech emerges at an early point in the process of language acquisition and remains stable for both native and non-native speech throughout early development. A sensitivity analysis of the meta-analytic data, however, indicates that a moderate publication bias for significant results could shift the lower credible interval to include null effects. Based on these findings, we outline recommendations for new lines of enquiry and suggest ways to improve the replicability of results in future investigations.

Detecting affiliation in colaughter across 24 societies.

Laughter is a nonverbal vocal expression that often communicates positive affect and cooperative intent in humans. Temporally coincident laughter occurring within groups is a potentially rich cue of affiliation to overhearers. We examined listeners' judgments of affiliation based on brief, decontextualized instances of colaughter between either established friends or recently acquainted strangers. In a sample of 966 participants from 24 societies, people reliably distinguished friends from strangers with an accuracy of 53-67%. Acoustic analyses of the individual laughter segments revealed that, across cultures, listeners' judgments were consistently predicted by voicing dynamics, suggesting perceptual sensitivity to emotionally triggered spontaneous production. Colaughter affords rapid and accurate appraisals of affiliation that transcend cultural and linguistic boundaries, and may constitute a universal means of signaling cooperative relationships.

The Perception of Spontaneous and Volitional Laughter Across 21 Societies.

Laughter is a nonverbal vocalization occurring in every known culture, ubiquitous across all forms of human social interaction. Here, we examined whether listeners around the world, irrespective of their own native language and culture, can distinguish between spontaneous laughter and volitional laughter-laugh types likely generated by different vocal-production systems. Using a set of 36 recorded laughs produced by female English speakers in tests involving 884 participants from 21 societies across six regions of the world, we asked listeners to determine whether each laugh was real or fake, and listeners differentiated between the two laugh types with an accuracy of 56% to 69%. Acoustic analysis revealed that sound features associated with arousal in vocal production predicted listeners' judgments fairly uniformly across societies. These results demonstrate high consistency across cultures in laughter judgments, underscoring the potential importance of nonverbal vocal communicative phenomena in human affiliation and cooperation.

Trails of meaning construction: Symbolic artifacts engage the social brain.

Symbolic artifacts present a challenge to theories of neurocognitive processing due to their hybrid nature: they are at the same time physical objects and vehicles of intangible social meanings. While their physical properties can be read of their perceptual appearance, the meaning of symbolic artifacts depends on the perceiver's interpretative attitude and embeddedness in cultural practices. In this study, participants built models of LEGO bricks to illustrate their understanding of abstract concepts. They were then scanned with fMRI while presented to photographs of their own and others' models. When participants attended to the meaning of the models in contrast to their bare physical properties, we observed activations in mPFC and TPJ, areas often associated with social cognition, and IFG, possibly related to semantics. When contrasting own and others' models, we also found activations in precuneus, an area associated with autobiographical memory and agency, while looking at one's own collective models yielded interaction effects in rostral ACC, right IFG and left Insula. Interestingly, variability in the insula was predicted by individual differences in participants' feeling of relatedness to their fellow group members during LEGO construction activity. Our findings support a view of symbolic artifacts as neuro-cognitive trails of human social interactions.

Reading Processes of University Students with Dyslexia - An Examination of the Relationship between Oral Reading and Reading Comprehension.

The purpose of this study was to examine the quality of oral reading and how it relates to reading comprehension in students with dyslexia. A group of Danish university students with dyslexia (n = 16) and a comparison group of students with no history of reading problems (n = 16) were assessed on their oral reading performance when reading a complex text. Along with reading speed, we measured not only the number and quality of reading errors but also the extent and semantic nature of the self-corrections during reading. The reading comprehension was measured through aided text retellings. The results showed that, as a group, the dyslexics performed poorer on most measures, but there were notable within-group differences in the reading behaviours and little association between how well university students with dyslexia read aloud and comprehended the text. These findings suggest that many dyslexics in higher education tend to focus their attention on one subcomponent of the reading process, for example, decoding or comprehension, because engaging in both simultaneously may be too demanding for them. Copyright © 2016 John Wiley & Sons, Ltd.

Does interaction matter? Testing whether a confidence heuristic can replace interaction in collective decision-making.

In a range of contexts, individuals arrive at collective decisions by sharing confidence in their judgements. This tendency to evaluate the reliability of information by the confidence with which it is expressed has been termed the 'confidence heuristic'. We tested two ways of implementing the confidence heuristic in the context of a collective perceptual decision-making task: either directly, by opting for the judgement made with higher confidence, or indirectly, by opting for the faster judgement, exploiting an inverse correlation between confidence and reaction time. We found that the success of these heuristics depends on how similar individuals are in terms of the reliability of their judgements and, more importantly, that for dissimilar individuals such heuristics are dramatically inferior to interaction. Interaction allows individuals to alleviate, but not fully resolve, differences in the reliability of their judgements. We discuss the implications of these findings for models of confidence and collective decision-making.

Different in different ways: A network-analysis approach to voice and prosody in Autism Spectrum Disorder.

The current study investigated whether the difficulty in finding group differences in prosody between speakers with autism spectrum disorder (ASD) and neurotypical (NT) speakers might be explained by identifying different acoustic profiles of speakers which, while still perceived as atypical, might be characterized by different acoustic qualities. We modelled the speech from a selection of speakers (N = 26), with and without ASD, as a network of nodes defined by acoustic features. We used a community-detection algorithm to identify clusters of speakers who were acoustically similar and compared these clusters with atypicality ratings by naïve and expert human raters. Results identified three clusters: one primarily composed of speakers with ASD, one of mostly NT speakers, and one comprised of an even mixture of ASD and NT speakers. The human raters were highly reliable at distinguishing speakers with and without ASD, regardless of which cluster the speaker was in. These results suggest that community-detection methods using a network approach may complement commonly-employed human ratings to improve our understanding of the intonation profiles in ASD.

Evidence for Infant-directed Speech Preference Is Consistent Across Large-scale, Multi-site Replication and Meta-analysis.

There is substantial evidence that infants prefer infant-directed speech (IDS) to adult-directed speech (ADS). The strongest evidence for this claim has come from two large-scale investigations: i) a community-augmented meta-analysis of published behavioral studies and ii) a large-scale multi-lab replication study. In this paper, we aim to improve our understanding of the IDS preference and its boundary conditions by combining and comparing these two data sources across key population and design characteristics of the underlying studies. Our analyses reveal that both the meta-analysis and multi-lab replication show moderate effect sizes (d ≈ 0.35 for each estimate) and that both of these effects persist when relevant study-level moderators are added to the models (i.e., experimental methods, infant ages, and native languages). However, while the overall effect size estimates were similar, the two sources diverged in the effects of key moderators: both infant age and experimental method predicted IDS preference in the multi-lab replication study, but showed no effect in the meta-analysis. These results demonstrate that the IDS preference generalizes across a variety of experimental conditions and sampling characteristics, while simultaneously identifying key differences in the empirical picture offered by each source individually and pinpointing areas where substantial uncertainty remains about the influence of theoretically central moderators on IDS preference. Overall, our results show how meta-analyses and multi-lab replications can be used in tandem to understand the robustness and generalizability of developmental phenomena.

Quantifying the interplay of conversational devices in building mutual understanding.

Humans readily engage in idle chat and heated discussions and negotiate tough joint decisions without ever having to think twice about how to keep the conversation grounded in mutual understanding. However, current attempts at identifying and assessing the conversational devices that make this possible are fragmented across disciplines and investigate single devices within single contexts. We present a comprehensive conceptual framework to investigate conversational devices, their relations, and how they adjust to contextual demands. In two corpus studies, we systematically test the role of three conversational devices: backchannels, repair, and linguistic entrainment. Contrasting affiliative and task-oriented conversations within participants, we find that conversational devices adaptively adjust to the increased need for precision in the latter: We show that low-precision devices such as backchannels are more frequent in affiliative conversations, whereas more costly but higher-precision mechanisms, such as specific repairs, are more frequent in task-oriented conversations. Further, task-oriented conversations involve higher complementarity of contributions in terms of the content and perspective: lower semantic entrainment and less frequent (but richer) lexical and syntactic entrainment. Finally, we show that the observed variations in the use of conversational devices are potentially adaptive: pairs of interlocutors that show stronger linguistic complementarity perform better across the two tasks. By combining motivated comparisons of several conversational contexts and theoretically informed computational analyses of empirical data the present work lays the foundations for a comprehensive conceptual framework for understanding the use of conversational devices in dialogue. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Behavioral excess and disruptive conduct: A historical and taxonomic approach to the origin of the 'impulse control disorders' diagnostic construct.

AIMS: Impulse control disorders (ICDs) are iatrogenic and idiopathic conditions with psychosocial and economic consequences for the affected individuals and their families (e.g. bankruptcy and divorce). However, the definition of ICDs has changed over time, and ICDs are not consistently included within existing taxonomies. We discuss the origins of the ICD diagnostic construct and its unsolved tensions. METHODS: To contextualize the ICD diagnostic construct, we provided an overview of its origins in past centuries and followed its development across multiple editions of the Diagnostic and Statistical Manual and the International Classification of Diseases, as well as its definition within emerging ontologies. RESULTS: Two independent roots of the ICD construct emerged: (a) the interest in behavioral excess as expressed in encyclopedic compilations (18th century) and (b) the juridical debate on disruptive conduct and responsibility (19th-20th centuries). These roots underlie the repeated taxonomic remodeling observed throughout the 20th and 21st centuries and three critical issues persisting in both clinical practice and research. First, the number of ICDs keeps increasing across the spectrum of human behaviors, disregarding common pathogenetic and phenomenological grounds. Secondly, ICDs substantially overlap with other mental conditions. Impulsivity is often neglected as a minor inconvenience or side effect when co-occurring with major diagnoses (e.g. depression) and therefore inadequately managed. Finally, ICDs' definitions display an unsolved tension between being conceived as hobby, moral fault or pathological drive, which may be responsible for stigma and delayed intervention. CONCLUSION: The reasons that made impulse control disorders (ICDs) difficult to define from their first conceptualization are the same reasons that now complicate taxonomic efforts and diagnosis. Tracing back ICDs' roots and criticalities can help to define a common and less ambiguous theoretical framework, which may also result in the demise of the ICD construct and a move towards more clearly defined and more useful ontologies.

The Social Route to Abstraction: Interaction and Diversity Enhance Performance and Transfer in a Rule-Based Categorization Task.

Capacities for abstract thinking and problem-solving are central to human cognition. Processes of abstraction allow the transfer of experiences and knowledge between contexts helping us make informed decisions in new or changing contexts. While we are often inclined to relate such reasoning capacities to individual minds and brains, they may in fact be contingent on human-specific modes of collaboration, dialogue, and shared attention. In an experimental study, we test the hypothesis that social interaction enhances cognitive processes of rule-induction, which in turn improves problem-solving performance. Through three sessions of increasing complexity, individuals and groups were presented with a problem-solving task requiring them to categorize a set of visual stimuli. To assess the character of participants' problem representations, after each training session, they were presented with a transfer task involving stimuli that differed in appearance, but shared relations among features with the training set. Besides, we compared participants' categorization behaviors to simulated agents relying on exemplar learning. We found that groups performed superior to individuals and agents in the training sessions and were more likely to correctly generalize their observations in the transfer phase, especially in the high complexity session, suggesting that groups more effectively induced underlying categorization rules from the stimuli than individuals and agents. Crucially, variation in performance among groups was predicted by semantic diversity in members' dialogical contributions, suggesting a link between social interaction, cognitive diversity, and abstraction.

The Dynamic Interplay of Kinetic and Linguistic Coordination in Danish and Norwegian Conversation.

In conversation, individuals work together to achieve communicative goals, complementing and aligning language and body with each other. An important emerging question is whether interlocutors entrain with one another equally across linguistic levels (e.g., lexical, syntactic, and semantic) and modalities (i.e., speech and gesture), or whether there are complementary patterns of behaviors, with some levels or modalities diverging and others converging in coordinated fashions. This study assesses how kinematic and linguistic entrainment interact with one another across levels of measurement, and according to communicative context. We analyzed data from two matched corpora of dyadic interaction between-respectively-Danish and Norwegian native speakers engaged in affiliative conversations and task-oriented conversations. We assessed linguistic entrainment at the lexical, syntactic, and semantic level, and kinetic alignment of the head and hands using video-based motion tracking and dynamic time warping. We tested whether-across the two languages-linguistic alignment correlates with kinetic alignment, and whether these kinetic-linguistic associations are modulated either by the type of conversation or by the language spoken. We found that kinetic entrainment was positively associated with low-level linguistic (i.e., lexical) entrainment, while negatively associated with high-level linguistic (i.e., semantic) entrainment, in a cross-linguistically robust way. Our findings suggest that conversation makes use of a dynamic coordination of similarity and complementarity both between individuals as well as between different communicative modalities, and provides evidence for a multimodal, interpersonal synergy account of interaction.

Caregiver linguistic alignment to autistic and typically developing children: A natural language processing approach illuminates the interactive components of language development.

BACKGROUND: Language development is a highly interactive activity. However, most research on linguistic environment has focused on the quantity and complexity of linguistic input to children, with current models showing that complexity facilitates language in both typically developing (TD) and autistic children. AIMS: After reviewing existing work on caregiver engagement of children's utterances, we aim to operationalize such engagement with automated measures of linguistic alignment, thereby providing scalable tools to assess caregivers' active reuse of their children's language. By assessing the presence of alignment, its sensitivity to the child's individual differences and how well it predicts language development beyond current models across the two groups, we showcase the usefulness of the approach and provide initial empirical foundations for further conceptual and empirical investigations. METHODS: We measure lexical, syntactic and semantic types of caregiver alignment in a longitudinal corpus involving 32 adult-autistic child and 35 adult-TD child dyads, with children between 2 and 5 years of age. We assess the extent to which caregivers repeat their children's words, syntax, and semantics, and whether these repetitions predict language development beyond more standard predictors. RESULTS: Caregivers tend to re-use their child's language in a way that is related to the child's individual, primarily linguistic, differences. Caregivers' alignment provides unique information improving our ability to predict future language development in both typical and autistic children. CONCLUSIONS: We provide evidence that language development also relies on interactive conversational processes, previously understudied. We share carefully detailed methods, and open-source scripts so as to systematically extend our approach to new contexts and languages.