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Differences in audiovisual integration are commonly observed in autism. Temporal binding windows (TBWs) of audiovisual speech can be trained (i.e., narrowed) in non-autistic adults; this study evaluated a computer-based perceptual training in autistic youth and assessed whether treatment outcomes varied according to individual characteristics. Thirty autistic youth aged 8-21 were randomly assigned to a brief perceptual training (n = 15) or a control condition (n = 15). At post-test, the perceptual training group did not differ, on average, on TBWs for trained and untrained stimuli and perception of the McGurk illusion compared to the control group. The training benefited youth with higher language and nonverbal IQ scores; the training caused widened TBWs in youth with co-occurring cognitive and language impairments.

BACKGROUND: Differences in responding to sensory stimuli, including sensory hyperreactivity (HYPER), hyporeactivity (HYPO), and sensory seeking (SEEK) have been observed in autistic individuals across sensory modalities, but few studies have examined the structure of these supra-modal traits in the autistic population. METHODS: Leveraging a combined sample of 3868 autistic youth drawn from 12 distinct data sources (ages 3-18 years and representing the full range of cognitive ability), the current study used modern psychometric and meta-analytic techniques to interrogate the latent structure and correlates of caregiver-reported HYPER, HYPO, and SEEK within and across sensory modalities. Bifactor statistical indices were used to both evaluate the strength of a general response pattern factor for each supra-modal construct and determine the added value of modality-specific response pattern scores (e.g., Visual HYPER). Bayesian random-effects integrative data analysis models were used to examine the clinical and demographic correlates of all interpretable HYPER, HYPO, and SEEK (sub)constructs. RESULTS: All modality-specific HYPER subconstructs could be reliably and validly measured, whereas certain modality-specific HYPO and SEEK subconstructs were psychometrically inadequate when measured using existing items. Bifactor analyses supported the validity of a supra-modal HYPER construct (ωH = .800) but not a supra-modal HYPO construct (ωH = .653), and supra-modal SEEK models suggested a more limited version of the construct that excluded some sensory modalities (ωH = .800; 4/7 modalities). Modality-specific subscales demonstrated significant added value for all response patterns. Meta-analytic correlations varied by construct, although sensory features tended to correlate most with other domains of core autism features and co-occurring psychiatric symptoms (with general HYPER and speech HYPO demonstrating the largest numbers of practically significant correlations). LIMITATIONS: Conclusions may not be generalizable beyond the specific pool of items used in the current study, which was limited to caregiver report of observable behaviors and excluded multisensory items that reflect many real-world sensory experiences. CONCLUSION: Of the three sensory response patterns, only HYPER demonstrated sufficient evidence for valid interpretation at the supra-modal level, whereas supra-modal HYPO/SEEK constructs demonstrated substantial psychometric limitations. For clinicians and researchers seeking to characterize sensory reactivity in autism, modality-specific response pattern scores may represent viable alternatives that overcome many of these limitations.

Purpose: Caregivers of autistic children present with high stress levels, which have been associated with poorer child outcomes in several domains, including language development. However, prior to this study, it was unknown whether elevated caregiver stress was associated with language development in infant siblings of autistic children (Sibs-autism), who are at increased likelihood of receiving a future diagnosis of autism and/or language impairment compared to infant siblings of non-autistic children. This study explored the degree to which, as well as the mechanisms by which, caregiver stress was linked with later language outcomes of Sibs-autism and infant siblings of non-autistic children (Sibs-NA). Method: Participants were 50 infants (28 Sibs-autism; 22 Sibs-NA) aged 12-- 18 months at the first time point in this study (Time 1). Infants were seen again 9 months later, at 21--27 months of age (Time 2). Caregiver stress was measured via a validated self-report measure at Time 1. Caregiver language input, the putative mechanism by which caregiver stress may influence later language outcomes, was collected via two daylong recordings from digital recording (Language ENvironment Analysis) devices worn by the child at this same time point. Child language outcomes were measured via standardized and caregiver report measures at Time 2. Results: Several models testing hypothesized indirect effects of caregiver stress on later child language outcomes through caregiver language input were statistically significant. Specifically, significant indirect effects suggest that (a) caregivers with increased stress tend to speak less to their infants, and (b) this reduced language input tends to covary with reduced child language outcomes later in life for Sibs-autism and Sibs-NA. Conclusions: This study provides new insights into links between caregiver stress, caregiver language input, and language outcomes in Sibs-autism and Sibs-NA. Further work is necessary to understand how to best support caregivers and optimize the language learning environments for infants.

How effective do observers expect other problem solvers to be? What makes a decision seem "human"?" We addressed this question in the context of the Traveling Salesman Problem (TSP), a decision problem in which a perfectly optimal solution is intractable, but for which various kinds of approximate solutions are available. We conducted a series of experiments involving both "production tasks" in which we asked subjects to solve the TSP, and "perception tasks", in which we asked subjects to judge others' solutions to the TSP, rating them for intelligence or humanness. Results suggest that observers expect human solutions to be less optimal than algorithmic solutions: observers expect human problem solvers to exhibit a combination of local and global solution criteria, and to use a short look-ahead window when choosing a solution. These results shed light on human models of other humans' minds, a fundamental problem in social interaction and robotics.

Children with autism show alterations in multisensory integration that have been theoretically and empirically linked with the core and related features of autism. It is unclear, however, to what extent multisensory integration maps onto features of autism within children with and without autism. This study, thus, evaluates relations between audiovisual integration and core and related autism features across children with and without autism. Thirty-six children reported perceptions of the McGurk illusion during a psychophysical task. Parents reported on participants' autistic features. Increased report of illusory percepts tended to covary with reduced autistic features and greater communication skill. Some relations, though, were moderated by group. This work suggests that associations between multisensory integration and higher-order skills are present, but in some instances vary according to diagnostic group.

Although the Traveling Salesman Problem (TSP) is an NP-hard problem, human schedulers can find strategies that are comparable if not better than existing algorithms. However, it is still unclear what heuristics they adopt in order to select an approximate solution (Schaefer, 2018). In solving a navigational problem in 3D, the directional heading is an essential factor because changes of direction require additional energy expenditure. In our study, we focus on the connection between local choices minimizing distance and local choices minimizing the turning angle. We then examine human solutions to the TSP in light of the tradeoff between local and global optimization of distance and turning angle. We conducted two experiments showing that while subjects were more likely to move to the nearest node when they plan the next step ahead, they also take the turning angle into consideration and overall adopt a strategy that combines local and global heuristics.

Looking to the mouth of a talker early in life predicts expressive communication. We hypothesized that looking at a talker's mouth may signal that infants are ready for increased supported joint engagement and that it subsequently facilitates prelinguistic vocal development and translates to broader gains in expressive communication. We tested this hypothesis in 50 infants aged 6-18 months with the heightened and general population-level likelihood of autism diagnosis (Sibs-autism and Sibs-NA; respectively). We measured infants' gaze to a speaker's face using an eye-tracking task, supported joint engagement during parent--child free play sessions, vocal complexity during a communication sample, and broader expressive communication. Looking at the mouth was indirectly associated with expressive communication via increased higher-order supported joint engagement and vocal complexity. This indirect effect did not vary according to sibling status. This study provides preliminary insights into the mechanisms by which looking at the mouth may influence expressive communication development.

When integrating information in real time from multiplemodalities or sources, such as when navigating with the helpof GPS voice instructions along with a visual map, a decision-maker is faced with a difficult cue integration problem. Thetwo sources, in this case visual and spoken, have potentiallyvery different interpretations or presumed reliability. Whenmaking decisions in real time, how do we combine cues com-ing from visual and linguistic evidence sources? In a sequenceof three studies we asked participants to navigate through aset of virtual mazes using a head-mounted virtual reality dis-play. Each maze consisted of a series of T intersections, ateach of which the subject was presented with a visual cue and aspoken cue, each separately indicating which direction to con-tinue through the maze. However the two cues did not alwaysagree, forcing the subject to make a decision about which cueto “trust.” Each type of cue had a certain level of reliability(probability of providing correct guidance), independent fromthe other cue. Subjects learned over the course of trials howmuch to follow each cue, but we found that they generallytrusted spoken cues more than visual ones, notwithstandingthe objectively matched reliability levels. Finally, we showhow subjects’ tendency to favor the spoken cue can be mod-eled as a Bayesian prior favoring trusting such sources morethan visual ones.

Purpose: Differences in communication development impact long-term outcomes of children with autism. Previous research has identified factors associated with communication in children with autism, but much of the variance in communication skill remains unexplained. It has been proposed that early differences in sensory responsiveness (i.e., hyporesponsiveness, hyperresponsiveness, and sensory seeking) may produce "cascading effects" on communication. Evidence for this theory is limited, however, as relations between sensory responsiveness and communication in the earliest stages of development have not been well established. The purpose of this study was to evaluate: (1) whether infants with a heightened likelihood of autism diagnosis (i.e., infants with an older sibling with autism) differ from infants at general population--level likelihood of autism (i.e., infants with an older, nonautistic sibling) on patterns of sensory responsiveness; (2) whether early sensory responsiveness is correlated with concurrent communication; and (3) whether the aforementioned between-groups differences and associations are moderated by age. Method: Participants were 40 infants (20 infants with an older sibling with autism, 20 infants with an older, nonautistic sibling) aged 12-18 months. A series of observational and parent report measures of sensory responsiveness and communication skill were administered. Results: Group differences in sensory responsiveness across the 12- to 18-month period were limited (i.e., only observed for one measure of hyporesponsiveness), though selected differences in sensory responsiveness (i.e., parent-reported hyperresponsiveness and sensory seeking) emerged between groups over this developmental window. Parent-reported hyporesponsiveness was unconditionally, negatively associated with communication skills. Associations between expressive communication and: (1) parent-reported sensory seeking; and (2) an observational measure of hyperresponsiveness were moderated by age. Conclusions: This study provides new insights into the nature of sensory responsiveness and theorized links with communication skill in infants at elevated and general population--level likelihood of autism diagnosis. Further work is needed to better characterize the effects of interest in a larger sample spanning a wider age range.

Children with autism spectrum disorder (ASD) display differences in multisensory function as quantified by several different measures. This study estimated the stability of variables derived from commonly used measures of multisensory function in school-aged children with ASD. Participants completed: a simultaneity judgment task for audiovisual speech, tasks designed to elicit the McGurk effect, listening-in-noise tasks, electroencephalographic recordings, and eye-tracking tasks. Results indicate the stability of indices derived from tasks tapping multisensory processing is variable. These findings have important implications for measurement in future research. Averaging scores across repeated observations will often be required to obtain acceptably stable estimates and, thus, to increase the likelihood of detecting effects of interest, as it relates to multisensory processing in children with ASD.

Purpose: This study synthesized effects of interventions on language outcomes of young children (ages 0-8 years) with autism and evaluated the extent to which summary effects varied by intervention, participant, and outcome characteristics. Method: A subset of effect sizes gathered for a larger meta-analysis (the Autism Intervention Meta-analysis or Project AIM) examining the effects of interventions for young children with autism, which were specific to language outcomes, was analyzed. Robust variance estimation and metaregression were used to calculate summary and moderated effects while controlling for intercorrelation among outcomes within studies. Results: A total of 221 outcomes were gathered from 60 studies. The summary effect of intervention on language outcomes was small but significant. Summary effects were larger for expressive and composite language outcomes compared to receptive language outcomes. Interventions implemented by clinicians, or by clinicians and caregivers together, had summary effects that were significantly larger than interventions implemented by caregivers alone. Participants' pretreatment language age equivalent scores positively and significantly moderated intervention effects, such that effects were significantly larger on average when samples of children had higher pretreatment language levels. Effects were not moderated by cumulative intervention intensity, intervention type, autism symptomatology, chronological age, or the proximity or boundedness of outcomes. Study quality concerns were apparent for a majority of included outcomes. Conclusions: We found evidence that intervention can facilitate improvements in language outcomes for young children with autism. Effects were largest for expressive and composite language outcomes, for children with initially higher language abilities, and for interventions implemented by clinicians or by caregivers and clinicians combined. However, quality concerns of included studies and borderline significance of some results temper our conclusions regarding intervention effectiveness and corresponding moderators.

Many studies have demonstrated that motion can convey intentionality and mental goals; for example, how do we distin-guish between a moving avatar thats controlled by a human being and a moving AI agent thats controlled by a computer?To answer this question, we use the travelling salesman problem (TPS), since it has been widely studied and, when thenumber of targets is limited, can be resolved optimally by both computers and human beings, even though with the useof different computational strategies (MacGregor & Chu, 2000). We asked 25 online participants to evaluate the perfor-mance of 5 human subjects and one AI agent in solving the TSP. The performances varied in efficiency. Results show thatoptimality is correlated with the perceived humanness of the agent: a lower efficiency in carrying out the task is perceivedas a distinctly human characteristic. Future directions include the analysis of the agent’s gaze direction.

Research shows that children with autism spectrum disorder (ASD) differ in their behavioral patterns of responding to sensory stimuli (i.e., sensory responsiveness) and in various other aspects of sensory functioning relative to typical peers. This study explored relations between measures of sensory responsiveness and multisensory speech perception and integration in children with and without ASD. Participants were 8-17 year old children, 18 with ASD and 18 matched typically developing controls. Participants completed a psychophysical speech perception task, and parents reported on children's sensory responsiveness. Psychophysical measures (e.g., audiovisual accuracy, temporal binding window) were associated with patterns of sensory responsiveness (e.g., hyporesponsiveness, sensory seeking). Results indicate that differences in multisensory speech perception and integration covary with atypical patterns of sensory responsiveness.

We conducted a multi-pronged investigation of different types of reporting bias in autism early childhood intervention research. First, we investigated the prevalence of reporting failures of completed trials registered on clinicaltrials.gov, and found that only 7% of registered trials were updated with results on the registration platform and only 64% had associated published reports. Next, we investigated the extent to which inadequate reporting prevents inclusion in meta-analytic summary estimates by identifying reports of studies that were eligible for inclusion in a prior meta-analysis, and found that 25% were excluded due to inadequate reporting. Finally, we investigated selective reporting practices by analyzing the protocols of the studies included in the meta-analysis which had been registered on any trial registry and coding their timing, completeness, and consistency. We found that 23% of studies were pre-registered, 71% were late-registered, and 5% were registered at an unclear date. Only 8% of registrations specified all of the necessary components. Evidence of selective reporting was common; 36% failed to report a registered outcome, 61% reported unregistered outcomes, 23% switched primary and secondary outcomes, and 43% had assessment timepoints that differed from registration specification. Given the inadequacy of registration and reporting practices, we offer practical recommendations to facilitate improvement for the field of autism research. When researchers fail to report their findings or only report some of their findings, it can make it difficult for clinicians to provide effective intervention recommendations. However, no one has examined whether this is a problem in studies of early childhood autism interventions. We studied how researchers that study early childhood autism interventions report their findings. We found that most researchers did not register their studies when they were supposed to (before the start of the study), and that many researchers did not provide all of the needed information in the registration. We also found that researchers frequently did not publish their findings when their studies were complete. When we looked at published reports, we found that many of the studies did not report enough information, and that many studies were reported differently from their registrations, suggesting that researchers were selectively reporting positive outcomes and ignoring or misrepresenting less positive outcomes. Because we found so much evidence that researchers are failing to report their findings quickly and correctly, we suggested some practical changes to make it better. [ABSTRACT FROM AUTHOR]

Augmenting the Modeling Power of the Multinomial Logit Model Using choice models to capture customer choice behavior has steadily become the common practice in revenue management. Discrete choice models allow one to capture the fact that customers substitute among the offered products, so if a particular product is not offered, then a portion of the customers interested in this product will substitute into a suitable available alternative. The multinomial logit model is one of the most commonly used choice models to capture customer choice in practice. This choice model is based on the utility maximization framework. A customer associates random utilities with the products, as well as the no-purchase option, in which case, the customer purchases the product with the largest utility, as long as its utility exceeds that of the no-purchase option. In "Assortment Optimization under the Multinomial Logit Model with Utility-Based Rank Cutoffs," Bai, Feldman, Topaloglu, and Wagner augment the modeling flexibility of the multinomial logit model, where a customer also leaves without a purchase if she cannot find one of her top few choices. They develop algorithms to find revenue-maximizing assortments. We study assortment optimization problems under a natural variant of the multinomial logit model where the customers are willing to focus only on a certain number of products that provide the largest utilities. In particular, each customer has a rank cutoff, characterizing the number of products that she will focus on during the course of her choice process. Given that we offer a certain assortment of products, the choice process of a customer with rank cutoff k proceeds as follows. The customer associates random utilities with all of the products as well as the no-purchase option. The customer ignores all alternatives whose utilities are not within the k largest utilities. Among the remaining alternatives, the customer chooses the available alternative that provides the largest utility. Under the assumption that the utilities follow Gumbel distributions with the same scale parameter, we provide a recursion to compute the choice probabilities. Considering the assortment optimization problem to find the revenue-maximizing assortment of products to offer, we show that the problem is NP-hard and give a polynomial time approximation scheme. Because the customers ignore the products below their rank cutoffs in our variant of the multinomial logit model, intuitively speaking, our variant captures choosier choice behavior than the standard multinomial logit model. Accordingly, we show that the revenue-maximizing assortment under our variant includes the revenue-maximizing assortment under the standard multinomial logit model, so choosier behavior leads to larger assortments offered to maximize the expected revenue. We conduct computational experiments on both synthetic and real data sets to demonstrate that incorporating rank cutoffs can yield better predictions of customer choices and yield more profitable assortment recommendations. Funding: The work of Y. Bai and H. Topaloglu was partially supported by the National Science Foundation [Grant No. CMMI-1825406]. Supplemental Material: The e-companion is available at https://doi.org/10.1287/opre.2021.0060. [ABSTRACT FROM AUTHOR]

Purpose: One manifestation of systemic inequities in communication sciences and disorders (CSD) is the chronic underreporting and underrepresentation of sex, gender, race, and ethnicity in research. The present study characterized recent demographic reporting practices and representation of participants across CSD research. Method: We systematically reviewed and extracted key reporting and participant data from empirical studies conducted in the United States with human participants published in the year 2020 in journals by the American Speech- Language-Hearing Association (ASHA; 407 articles comprising a total of 80,058 research participants, search completed in November 2021). Sex, gender, race, and ethnicity were operationalized per National Institutes of Health guidelines. Results: Sex or gender was reported in 85.5% of included studies; race in 33.7%; and ethnicity in 13.8%. Sex and gender were clearly differentiated in 3.4% of relevant studies. Where reported, median proportions for race and ethnicity were significantly different from the U.S. population, with underrepresentation noted for all non-White racial groups and Hispanic participants. Moreover, 64.7% of studies that reported sex or gender and 67.2% of studies that reported race or ethnicity did not consider these respective variables in analyses or discussions. Conclusions: At present, research published in ASHA journals frequently fails to report key demographic data summarizing the characteristics of participants. Moreover, apparent gaps in the representation of minoritized racial and ethnic groups threaten the external validity of CSD research and broader health care equity endeavors in the United States. Although our study is limited to a single year and publisher, our results point to several steps for readers that may bring greater accountability, consistency, and diversity to the discipline. [ABSTRACT FROM AUTHOR]

The representation of complex phenomena via combinations of simple discrete features is a hallmark of human cognition. But it is not clear exactly how (or whether) discrete features can effectively represent the complex probabilistic fabric of the environment. This article introduces information-theoretic tools for quantifying the fidelity and efficiency of a featural representation with respect to a probability model. In this framework, a feature or combination of features is "faithful" to the extent that knowing the value of the features reduces uncertainty about the true state of the world. In a single dimension, a discrete feature is faithful if the values of the feature correspond isomorphically to distinct classes in the probability model. But in multiple dimensions, the situation is more complicated: The fidelity of each feature depends on the direction in multidimensional feature space in which the feature is projected from the underlying distribution. More interestingly, distributions may be more effectively represented by combinations of projected features—that is, compositionality. For any given distribution, a variety of compositional forms (features and combination rules) are possible, which can be quite different from one another, entailing different degrees of fidelity, different numbers of features, and even different induced regularities. This article proposes three specific criteria for a compositional representation: fidelity, simplicity, and robustness. The information-theoretic framework introduces a new and potentially useful way to look at the problem of compositionality in human mental representation. [ABSTRACT FROM AUTHOR]