School of Social Sciences, Humanities, and Arts

In everyday communication, speakers and listeners make sophisticated inferences about their conversation partner's intended meaning. They combine their knowledge of the visuospatial context with reasoning about the other person's knowledge state and rely on shared assumptions about how language is used to express communicative intentions. However, these assumptions may differ between languages of nonindustrialized-where conversations often primarily take place within a, so-called, society of intimates-and industrialized cultures-societies of strangers. Here, we study inference in communication in the Tsimane', an indigenous people of the Bolivian Amazon, who have little contact with industrialization or formal education. Using a referential communication task, we probe how Tsimane' speakers refer to objects in the world around them when there are potential ambiguities (e.g., referring to a cup when there are multiple cups in view) across different visual contexts. Using an eye-tracking task, we probe the real-time inferences that Tsimane' listeners make about the speaker's intentions. We find that Tsimane' speakers use visual (color, size) contrasts to disambiguate referents (e.g., "Hand me the small cup"), much like English speakers, and they predictively direct their gaze to objects in a contrast set when they hear a modifier (e.g., "small"). Despite myriad cultural and linguistic dissimilarities between the two populations, the qualitative patterns of behavior and eye-gaze of Tsimane' and English speakers were strikingly similar, suggesting that the communicative expectations underlying many everyday inferences may be shared across cultures. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

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Recent studies have questioned past conclusions regarding the mechanisms of the McGurk illusion, especially how McGurk susceptibility might inform our understanding of audiovisual (AV) integration. We previously proposed that the McGurk illusion is likely attributable to a default mechanism, whereby either the visual system, auditory system, or both default to specific phonemes-those implicated in the McGurk illusion. We hypothesized that the default mechanism occurs because visual stimuli with an indiscernible place of articulation (like those traditionally used in the McGurk illusion) lead to an ambiguous perceptual environment and thus a failure in AV integration. In the current study, we tested the default hypothesis as it pertains to the auditory system. Participants performed two tasks. One task was a typical McGurk illusion task, in which individuals listened to auditory-/ba/ paired with visual-/ga/ and judged what they heard. The second task was an auditory-only task, in which individuals transcribed trisyllabic words with a phoneme replaced by silence. We found that individuals' transcription of missing phonemes often defaulted to '/d/t/th/', the same phonemes often experienced during the McGurk illusion. Importantly, individuals' default rate was positively correlated with their McGurk rate. We conclude that the McGurk illusion arises when people fail to integrate visual percepts with auditory percepts, due to visual ambiguity, thus leading the auditory system to default to phonemes often implicated in the McGurk illusion.

The quantifier "some" often elicits a scalar implicature during comprehension: "Some of today's letters have checks inside" is often interpreted to mean that not all of today's letters have checks inside. In previous work, Goodman and Stuhlmüller (G&S) proposed a model that predicts that this implicature should depend on the speaker's knowledgeability: If the speaker has only examined some of the available letters (e.g., two of three letters), people are less likely to infer that "some" implies "not all" than if the speaker has examined all of the available letters. G&S also provided behavioral evidence in support of their model. In this paper, we first show that a simple extension of G&S's model (1) predicts G&S's knowledgeability effects, and in addition, (2) predicts that the knowledgeability effect will be reduced when the speaker's usage indicates numeral alternatives are available. We tested the new model's predictions in four preregistered experiments. All experiments supported the first model prediction, replicating G&S's finding of a main effect of the speaker's knowledge. Further, Experiments 2 and 4 supported the second model prediction showing that the words that a speaker tends to use affect the strength of scalar implicature that comprehenders make. In particular, when the speaker has partial knowledge (e.g., has only examined two of three letters), comprehenders think that "some" is more likely to mean "not all" when the speaker also tends to produce number words in similar sentences (e.g., "2 of today's rooms have working smoke detectors."). These results have important ramifications for theories of meaning: the context beyond the sentence (e.g., the speaker's tendency to use particular words) affects the set of alternatives that comprehenders consider when inferring meaning.

When interacting with infants, humans often alter their speech and song in ways thought to support communication. Theories of human child-rearing, informed by data on vocal signalling across species, predict that such alterations should appear globally. Here, we show acoustic differences between infant-directed and adult-directed vocalizations across cultures. We collected 1,615 recordings of infant- and adult-directed speech and song produced by 410 people in 21 urban, rural and small-scale societies. Infant-directedness was reliably classified from acoustic features only, with acoustic profiles of infant-directedness differing across language and music but in consistent fashions. We then studied listener sensitivity to these acoustic features. We played the recordings to 51,065 people from 187 countries, recruited via an English-language website, who guessed whether each vocalization was infant-directed. Their intuitions were more accurate than chance, predictable in part by common sets of acoustic features and robust to the effects of linguistic relatedness between vocalizer and listener. These findings inform hypotheses of the psychological functions and evolution of human communication.

The evolutionary fitness payoffs of moral condemnation are greatest within an individual's immediate social milieu. Accordingly, insofar as human moral intuitions have been shaped by adaptive design, we can expect transgressive harms to be perceived as more wrong when transpiring in the here and now than when occurring at a distance, or with the approval of local authority figures. This moral parochialism hypothesis has been supported by research conducted in diverse societies, but has yet to be tested in an East Asian society, despite prior research indicating that East Asians appraise transgressive acts as being caused by situational and contextual factors to a greater extent than do Westerners, who tend to emphasize dispositional factors (i.e., the transgressor's personal nature). Here, in a quasi-experiment using field samples recruited in Seoul and Los Angeles, we tested (i) the moral parochialism hypothesis regarding the perceived wrongness of transgressions, as well as (ii) the extent to which these wrongness judgments might be influenced by cross-cultural differences in causal appraisals. Despite notably large differences across the two societies in situational versus dispositional appraisals of the causes of the transgressions, replicating previous findings elsewhere, in both societies we found that transgressions were deemed less wrong when occurring at spatial or temporal remove or with the consent of authorities. These findings add to the understanding of morality as universally focused on local affairs, notwithstanding cultural variation in perceptions of the situational versus dispositional causes of (im)moral acts.

When a population exhibits collective cognitive alignment, such that group members tend to perceive, remember, and reproduce information in similar ways, the features of socially transmitted variants (i.e., artifacts, behaviors) may converge over time towards culture-specific equilibria points, often called cultural attractors. Because cognition may be plastic, shaped through experience with the cultural products of others, collective cognitive alignment and stable cultural attractors cannot always be taken for granted, but little is known about how these patterns first emerge and stabilize in initially uncoordinated populations. We propose that stable cultural attractors can emerge from general principles of human categorization and communication. We present a model of cultural attractor dynamics, which extends a model of unsupervised category learning in individuals to a multiagent setting wherein learners provide the training input to each other. Agents in our populations spontaneously align their cognitive category structures, producing emergent cultural attractor points. We highlight three interesting behaviors exhibited by our model: (1) noise enhances the stability of cultural category structures; (2) short 'critical' periods of learning early in life enhance stability; and (3) larger populations produce more stable but less complex attractor landscapes, and cliquish network structure can mitigate the latter effect. These results may shed light on how collective cognitive alignment is achieved in the absence of shared, innate cognitive attractors, which we suggest is important to the capacity for cumulative cultural evolution.

This report is the second part of a comprehensive two-part series aimed at reviewing an extensive and diverse toolkit of novel methods to explore brain health and function. While the first report focused on neurophotonic tools mostly applicable to animal studies, here, we highlight optical spectroscopy and imaging methods relevant to noninvasive human brain studies. We outline current state-of-the-art technologies and software advances, explore the most recent impact of these technologies on neuroscience and clinical applications, identify the areas where innovation is needed, and provide an outlook for the future directions.

Significance: Resting-state functional connectivity (RSFC) analyses of functional near-infrared spectroscopy (fNIRS) data reveal cortical connections and networks across the brain. Motion artifacts and systemic physiology in evoked fNIRS signals present unique analytical challenges, and methods that control for systemic physiological noise have been explored. Whether these same methods require modification when applied to resting-state fNIRS (RS-fNIRS) data remains unclear. Aim: We systematically examined the sensitivity and specificity of several RSFC analysis pipelines to identify the best methods for correcting global systemic physiological signals in RS-fNIRS data. Approach: Using numerically simulated RS-fNIRS data, we compared the rates of true and false positives for several connectivity analysis pipelines. Their performance was scored using receiver operating characteristic analysis. Pipelines included partial correlation and multivariate Granger causality, with and without short-separation measurements, and a modified multivariate causality model that included a non-traditional zeroth-lag cross term. We also examined the effects of pre-whitening and robust statistical estimators on performance. Results: Consistent with previous work on bivariate correlation models, our results demonstrate that robust statistics and pre-whitening are effective methods to correct for motion artifacts and autocorrelation in the fNIRS time series. Moreover, we found that pre-filtering using principal components extracted from short-separation fNIRS channels as part of a partial correlation model was most effective in reducing spurious correlations due to shared systemic physiology when the two signals of interest fluctuated synchronously. However, when there was a temporal lag between the signals, a multivariate Granger causality test incorporating the short-separation channels was better. Since it is unknown if such a lag exists in experimental data, we propose a modified version of Granger causality that includes the non-traditional zeroth-lag term as a compromising solution. Conclusions: A combination of pre-whitening, robust statistical methods, and partial correlation in the processing pipeline to reduce autocorrelation, motion artifacts, and global physiology are suggested for obtaining statistically valid connectivity metrics with RS-fNIRS. Further studies should validate the effectiveness of these methods using human data.

Spoken language production involves selecting and assembling words and syntactic structures to convey one's message. Here we probe this process by analyzing natural language productions of individuals with primary progressive aphasia (PPA) and healthy individuals. Based on prior neuropsychological observations, we hypothesize that patients who have difficulty producing complex syntax might choose semantically richer words to make their meaning clear, whereas patients with lexicosemantic deficits may choose more complex syntax. To evaluate this hypothesis, we first introduce a frequency-based method for characterizing the syntactic complexity of naturally produced utterances. We then show that lexical and syntactic complexity, as measured by their frequencies, are negatively correlated in a large (n = 79) PPA population. We then show that this syntax-lexicon trade-off is also present in the utterances of healthy speakers (n = 99) taking part in a picture description task, suggesting that it may be a general property of the process by which humans turn thoughts into speech.