United States

The Response to Joint Attention (RJA) allows coordinating attention with a partner by following social cues as indicated by the gaze, head turn or gestures. One developmental hypothesis suggests that this ability may initially rely on the perception of head motion and refines until responding to the final gaze direction. The autism spectrum disorders (ASD) present reduced joint attention behaviors, the development of which is the goal of many therapeutic interventions and could benefit from a precise knowledge of how social cues trigger (or fail to trigger) the RJA.
In this study, we test the developmental hypothesis. We developed a computational model simulating gaze following tasks and explored the effect of differences in the amount of information and temporal dynamics of social and non-social cues. Our model is contrasted with previous empirical studies and it describes developmental trajectories of typical and atypical RJA.

CogSci 2021

Computational Analysis of Social Cues in the Response to Joint Attention, The More the Better

**31st IEEE International Conference on Robot & Human Interactive Communication**
 This conference is a leading forum where state-of-the-art innovative results, the latest developments as well as future perspectives relating to robot and human interactive communication are presented and discussed.
 
 The conference covers a wide range of topics related to Robot and Human Interactive Communication, involving theories, methodologies, technologies, empirical and experimental studies. Papers related to the study of robotic technology, psychology, cognitive science, artificial intelligence, human factors, ethics and policies, interaction-based robot design and other topics related to human-robot interaction are welcome.
 
 **CONFERENCE THEME:**
 Social, asocial, and antisocial robots
 
 Robots are starting to populate our lives: at work, in our homes, hotels, shops. However, not everybody is comfortable with robots finding a place in society. For example, people may be afraid that robots will replace humans in their jobs. This belief is exacerbated by the media that, on one side, raise expectations of robots’ capabilities, while amplifying fears and worries on the other side.
 
 In the next years, due to the increasing request for interaction with people in social environments, academic research and market analyses predict that robots will become more and more “social”. But, at the same time, robots may incur the risk of being perceived as “asocial” as their pervasiveness in everyday environments may become an obstacle to social interaction between humans. Or they may even be rejected as “antisocial” if researchers do not take care to develop robots that behave according to the customs and habits of the communities where they are expected to operate.
 
 To prevent this from happening, robotic researchers can no longer take the luxury of being mere technicians. They must be capable of addressing all the challenges raised by future robot-populated communities in a multidisciplinary way. They need to share their knowledge with the public to make people aware of what robots really are, what expectations we can have from them, the risks we may incur, and the possible mitigation plans.
 
 While being open to any kind of contribution related to Human-Robot Interactive Communication, the RO-MAN 2022 conference will emphasize these aspects of robotic research. How can we create robots capable of being welcomed as our assistants and companions in society while, at the same time, not being perceived as “asocial” or “antisocial?” How can we create robots perceived as facilitators of the natural development of human beings and communities, rather than obstacles?
 
 Contributions from different disciplines, not exclusively related to technological development, will be welcomed as crucial to pave the way to global acceptance of future robots with an informed attitude.
 
 [![](https://assets.underline.io/uploads/markdown_image/1/image/af259abe105b3791c498ae1552d75710.png)](https://drive.google.com/file/d/18w73BZPB_JVOgcrcdZDqYpEupwVt4CnU/view?usp=sharing)

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IEEE RO-MAN 2022

31st IEEE International Conference on Robot & Human Interactive Communication
This conference is a leading forum where state-of-the-art innovative results, the latest developments as well as future perspectives relating to robot and human interactive communication are presented and discussed.

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### Looking for Cogsci 2023? Please [click here](https://underline.io/events/405/reception) to switch to 2023 edition.


**Dear Colleagues,**

Welcome to the 43rd Annual Conference of the Cognitive Science Society! 

This year’s conference brings together the latest research from all Cognitive Science and also highlights this year’s theme **Comparative Cognition: Animal Minds.** 

The program features four plenary speakers: Friederike Range (University of Veterinary Medicine, Vienna), Onur Güntürkün (Ruhr University Bochum), Julia Fischer (University of Göttingen), and Erich Jarvis (The Rockefeller University). The keynotes and invited symposia showcase the broad spectrum of ideas that encompass the conference theme of comparative cognition. 

Further, the program includes the Rumelhart Prize keynote presentation by Susan Goldin-Meadow (University of Chicago), and symposia to celebrate the winner of the Elman Prize: Wei Ji Ma (New York University), the Heineken Award winner Robert Zatorre (McGill University), and the Robert J. Glushko Dissertation Prizes session.

The program committee for CogSci 2021 received 1,025 submissions, including 710 full papers, 275 member abstracts, 8 publication-based talks, as well as 15 proposals for symposia, and 17 for workshops and tutorials. After a rigorous review process, the committee selected 152 papers for oral presentation and inclusion in the conference proceedings (14.8%), 332 papers for poster presentation and inclusion in the proceedings (32.4%), and 175 papers for poster presentation with inclusion of abstracts in the proceedings (17.1%) We also selected 275 submitted member abstracts. In addition, we accepted 6 publication-based talks, 12 symposia, and 9 workshops and tutorials to make for an exciting and inclusive program.

We hope that you enjoy the conference this year! 

**Your Program Chairs,**
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**Learn more about the Vienna Cognitive Science Hub at the University of Vienna, hosts of CogSci 2021**

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To review the proceedings for the conference or review the searchable program, please visit the [website](https://cognitivesciencesociety.org/program/).

The Cognitive Science Society brings together researchers from around the world who hold a common goal: understanding the nature of the human mind. The mission of the Society is to promote Cognitive Science as a discipline, and to foster scientific interchange among researchers in various areas of study, including Artificial Intelligence, Linguistics, Anthropology, Psychology, Neuroscience, Philosophy, and Education. The Society is a non-profit professional organization and its activities include sponsoring an annual conference and publishing the journals Cognitive Science and TopiCS.

We investigated the effect of semantic information on word memory, using imageability and sensorimotor strength as predictors, with data from a mega-study of word recognition memory (Cortese et al., 2010; 2015), as well as from an online memory task. Memory performance was analysed in hierarchical linear regressions. Both sensorimotor strength and imageability had an effect on word memory performance, but not as strong as reported in previous literature. However, the effects were smaller when the memory task was unexpected, suggesting that the semantic effects are dependent on memory strategies (or context). Most importantly, different types of sensorimotor strength had a variable effect on memory, which was not in line with the prediction of the semantic richness effect, and highlighted the importance of a multi-dimensional approach to measuring and testing semantic experience, and its effect on cognitive processing. The findings have implications for the use of semantic variables in memory research.

More is not necessarily better – how different aspects of sensorimotor experience affect recognition memory for words

Deese/Roediger/McDermott (DRM) list words can share either semantic relatedness or phonological resemblance with their critical distractor. We review three lines of evidence in which semantic and phonological DRM illusions have been compared: (a) studies in which the two illusions were tracked in populations with different semantic or surface memory abilities; (b) studies that investigated the effects of manipulations that target semantic content or surface content or both; and (c) studies that examined hybrid forms of the illusion in which there was both semantic and surface resemblance between false memories and actual experiences. The three lines of evidence showed that semantic and phonological DRM illusions display dissociative patterns in most instances, indicating that they are two distinct types of false memories. We also discussed how the two major theories of the DRM illusion, fuzzy-trace theory and the activation/monitoring framework, account for the underlying mechanisms for the semantic and phonological illusions.

Semantic and Phonological False Memory: A Review of Theory and Data

We asked whether it is possible to simultaneously activate two timelines in the human mind. We hypothesized that the lateral (left-right) and sagittal (back-front) spatial dimensions can be coactivated and expected the congruent space-time mappings of each dimension (back-past front-future and left-past right-future), but not the non-coherent ones, to prime each other. Participants were asked to keep in mind the two spatial dimensions as discrete entities. Spanish speakers categorized the temporal reference of sentences by pressing a sagittal directional key with their left or right hand. Results suggest that (i) full congruence facilitates the spatial representation of time the most, (ii) full incongruence interferes the most with the spatial representation of time, and (iii)
the two partial forms of congruence produce similar interference effects between the two spatial dimensions and time. The results were interpreted according to the Coherent Working Models approach.

Do left-right and back-front mental timelines activate simultaneously?

There is broad empirical evidence suggesting that higher-level cognitive processes, such as language, categorization, and emotion, shape human visual perception. For example, categories that we acquire throughout lifetime have been found to alter our perceptual discriminations and distort perceptual processing. Here, we study categorical effects on perception by adapting the perceptual matching task to minimize the potential non-perceptual influences on the results. We found that the learned category-color associations bias human color matching judgments away from their category ideal on a color continuum. This effect, however, unequally biased two objects (probe and manipulator) that were simultaneously present on the screen, thus demonstrating a more nuanced picture of top-down influences on perception than has been assumed both by the theories of categorical perception and the El Greco methodological fallacy. We suggest that only the concurrent memory for visually present objects is subject to a contrast-from-caricature distortion due to category-association learning.

Categories affect color perception of only some simultaneously present objects

Dividing attention by loading working memory is an effective method of probing the declarative and procedural underpinnings of linguistic knowledge. The current study explores WM/DA effects on four specific L2 domains: morphology (aspect versus case), syntax and semantics (collocations). We contrast performance of 68 learners of Polish as a foreign language (L1 Chinese) in a grammaticality judgement task in baseline and divided attention conditions. We found corroborating evidence for heightened dependency on declarative memory in early (A2) L2 learners across all linguistic categories and in both experimental conditions. While the lexical judgement of more advanced (B1) learners also proved vulnerable to secondary-task interference, introduction of additional cognitive load had a positive effect on participants’ grammatical judgement, yielding more accurate responses in the aspect category. These results point towards the need for pursuing a new line of inquiry into a potentially facilitative role of cognitive load on L2 learners’ grammatical processing.

The ‘know-what’ and the ‘know-how’: importance of declarative and procedural memory systems in the L2 learning of morphology, syntax and semantics

Previous studies have manifested a strong relationship between socio-economic status (SES) and cognitive abilities in young children, however, the effects of SES on developed cognitive architecture remain less explored. The current study examined whether and how cognitive processing differs as a function of socioeconomic status in adults. The performance measured individuals from lower and higher SES (29.9 ± 8.2 years, Male = 81, Female = 19) on tests of working memory (Digit Span), visuo-spatial memory (visual retention and recognition) and executive functioning (Stroop test and Koh’s block test). Lower SES adults had significantly lower test scores on all the measures as compared to the higher SES adults. These findings suggest that lower SES individuals exhibit lower cognitive abilities as compared to the individuals associated with higher SES. The current findings append to the previous literature by demonstrating a significant interaction between SES and cognitive processing in adults.

Impact of Socio-Economic Status on Cognitive Processing

Machine learning offers techniques for predicting behavior, but has limited capability to use behavior, context, and domain knowledge to infer intentions and predict behavior trajectory (i.e., sequence of directed actions towards reaching goal) of humans in real time to assist in strategic planning. Some existing models of human goal inference (Zhi-Xuan, Mann, Silver, Tenenbaum, & Manshinghka, 2020) possess some of these capabilities, however, these models are typically evaluated in toy worlds, which limits our understanding of how these approaches would generalize to real-world domains. Here, we introduce a novel integration of Bayesian goal inference and a deep learning model used for joint estimation (OpenPose) to address this generalizability problem and evaluate how this integrated approach can infer the goals of humans in real-world environments. This exploration provides an opportunity to evaluate capabilities required for real-time goal inference in real world environments and can highlight benefits and limitations informing future research.

Exploring Online Goal Inference in Real World Environments

Memory is reliably enhanced for information read aloud compared with information read silently—this is known as the production effect. Theoretical accounts of this effect have been largely verbal in nature with very little exception, yet its robustness (and that of related phenomena) suggests that it is worth integrating into existing computational approaches to memory. A leading account of the production effect proposes that production leads to encoding of additional features at study and that these features are available at test to assist retrieval, conferring the observed memory benefit. We implement a version of this account into the Retrieving Effectively from Memory (REM) computational framework and examine its ability to capture key phenomena associated with the production effect. We compare and contrast the current implementation in REM with a pre-existing implementation of this effect in MINERVA2, in addition to discussing alternative conceptualizations and future work.

Modelling the production effect in recognition memory

Understanding how we judge effortfulness promises insight into the myriad choices we make each day. Here, we present research investigating a curious finding: In Dunn et al., 2019, individuals anticipated reading a single rotated word as more effortful than reading two upright words. This contravenes the expectation that the latter will take significantly longer. In Dunn et al. (2019) participants had limited experience engaging in the task beyond judging anticipated effort. In the present investigation participants performed demand selection and forced-choice tasks for which they read either one rotated or two upright words. We analyze results in terms of choice, accuracy, vocal onset time, and task duration. Participants still generally considered reading two words as less effortful (and preferable) to one rotated word but, interestingly, this tendency diminished as the task wore on. We discuss implications for understanding individuals’ effort-based choices.

Cognitive Effort and Preference: A Curious Case of Rotated Words

The study of mental representations of concepts has historically focused on the representations of the “average” person. Here, we shift away from this aggregate view and examine the principles of variability across people in conceptual representations. Using a database of millions of sketches by people worldwide, we ask what predicts whether people converge or diverge in their representations of a specific concept, and which kinds of concepts tend to be more or less variable. We find that larger and more dense populations tend to have less variable representations, and concepts high in valence and arousal tend to be less variable across people. Further, two countries tend to have people with more similar conceptual representations when they are linguistically, geographically, and culturally similar. Our work provides the first characterization of the principles of variability in shared meaning across a large, diverse sample of participants.

Computational Analysis of Social Cues in the Response to Joint Attention, The More the Better

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More is not necessarily better – how different aspects of sensorimotor experience affect recognition memory for words

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