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This paper presents a theoretical framework for modeling human visual attention. The framework&#39;s core claim is that three mechanisms drive attention: selection, which picks out an item for further processing; engagement, which tags a selected item as relevant or irrelevant to the current task; and enhancement, which increases sensitivity to task-relevant items and decreases sensitivity to task-irrelevant items. Building on these mechanisms, the framework is able to explain human performance on attentionally demanding tasks like visual search and multiple object tracking, and it supports a broad range of predictions about the interactions between such tasks.

CogSci 2021

Selection, Engagement, &amp; Enhancement: A Framework for Modeling Visual Attention

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**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!<br><br>

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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.

This paper presents a theoretical framework for modeling human visual attention. The framework's core claim is that three mechanisms drive attention: selection, which picks out an item for further processing; engagement, which tags a selected item as relevant or irrelevant to the current task; and enhancement, which increases sensitivity to task-relevant items and decreases sensitivity to task-irrelevant items. Building on these mechanisms, the framework is able to explain human performance on attentionally demanding tasks like visual search and multiple object tracking, and it supports a broad range of predictions about the interactions between such tasks.

Selection, Engagement, & Enhancement: A Framework for Modeling Visual Attention

poster

Seeking for information is a ubiquitous requirement of life. Here, we studied how chimpanzees––one of humans closest living relatives––explore initially unknown payoff distributions before making a final exploitative draw (see Hertwig et al., 2004). More specifically, across two conditions (stable and changing), chimpanzees (N=15) could explore a risky (outcome variance) and a safe (no variance) assortment, prior to making a decision. In the stable condition, the safe and risky assortment remained on the same side and the food in the same location across trials. In the changing condition, the side of the assortments, as well as the location of the food within the assortments changed. We investigated (1) whether chimpanzees explore changing more than stable environments and (2) which strategies they use to explore their environments. We will discuss our findings in light of the evolutionary roots of human exploration and decision making strategies.

How do chimpanzees explore their environment prior to a risky decision?

By re-evaluating Crow (2000)’s claim that “Schizophrenia [is] the price that Homo sapiens pays for language”, we suggest that displacement, the ability to refer to things and situations outside from here and now, partly realized through syntactic operation, could be related to the symptoms of schizophrenia. Mainly supported by episodic memory, displacement has been found in nonhuman animals, but more limited than that in humans. As a conserved subcortical region, the hippocampus plays a key role in episodic memory across species. Evidence in humans suggests that the parietal lobe and basal ganglia are also involved in episodic Memory. We propose that what makes human displacement more developed could rely on the better coordination between the hippocampus and the parietal lobe and basal ganglia. Given that all these areas taking part in language processing, displacement could have served as an interface between episodic memory and language.

Displacement and Evolution: A Neurocognitive and Comparative Perspective

Creativity is defined as the ability to produce an object/idea that is both original and appropriate to the context. How originality and appropriateness of production are integrated in creative cognitive processes is not understood. We propose that creativity involves an evaluative component based on individual preferences for appropriateness and originality of candidate ideas stemming from a generative component. Through behavioral experiments inspired by neuroeconomics and using computational modeling, we aimed to characterize this evaluative component. Participants had to generate creative word associations and then rate how much each of their responses was appropriate, original and how much they liked it. We found that the way individuals balanced appropriateness and originality to build a subjective value of their ideas was correlated with creative abilities. These findings provide new insights into how individual preferences can impact creativity.

The subjective value of creative outputs: appropriate or original?

Animal reading studies have shown that word/non-word decision behavior can be performed by baboons and pigeons, despite their inability to access phonological and semantic representations. Previous modeling work used different learning models (e.g., deep-learning architectures) to successfully reproduce baboon lexical decisions. More transparent investigations of the implemented representations underlying baboons’ behavior are currently missing, however. Here we apply the highly transparent Speechless Reader Model, which is motivated by human reading and its underlying neurocognitive processes, to existing baboon data. We implemented four variants that comprise different sets of representations—all four models implemented visual-orthographic prediction errors. In addition, one model included prediction errors derived from positional letter frequencies, one prediction errors constrained by specific letter sequences, and finally, a combinatory model combined all three prediction errors. We compared the models’ behavior to that of the baboons and thereby identified one model which most adequately mirrored the animals’ learning success. This model combined the image-based prediction error and the letter-based prediction error that also accounts for the transitional probabilities within the letter sequence. Thus, we can conclude that animals, similarly to humans, use prediction error representations that capture orthographic codes to implement efficient reading-like behavior.

Speechless Reader Model: A neurocognitive model for human reading reveals cognitive underpinnings of baboon lexical decision behavior.

Animals socially interact with each other using complex behavioral displays. To better understand the dynamics of these interactions, videos and animations on computer screens have been used as one of the interactive animals. While both of these offer more control, whether responses to such stimuli are similar to responses to live animals remains poorly understood. Here, using the song of the male zebra finch, a songbird, as an example of a complex behavioral display, we examine responses to videos and animations of female zebra finches. We show that male zebra finches sing to videos and animations of female zebra finches, and the properties of these songs are similar to songs directed towards live female zebra finches, especially for longer videos. Overall, these results highlight the potential of using videos and animations to better understand social interactions involved in the production of complex behavioral displays, like birdsong.

Using videos and animations to study zebra finch social behaviors

Learning to program is challenging, because it involves novel skills. In contrast to the majority of work focusing on code generation, we target the skill of code tracing. Code tracing involves simulating the high-level actions a computer takes when it executes the program, including the flow of execution through it and how variable values change as a result. Code tracing supports program comprehension and generation. However, many students do not code trace effectively. Our project investigates the utility of peer tutoring for the learning of code tracing. While this approach remains untested in this context, it has successfully been used in other domains to improve student learning. We will present qualitative data from a case study involving students tutoring each other to code trace. This work is the first step in the context of a broader project focused on identifying ways to help students learn to code.

Student collaboration during code tracing activities

Although representations of countable numerosities, i.e., number of elements in a set, have been deciphered down to single neurons, the neuronal representations of numerosity zero (empty set, ES) remain largely unknown. We probed the behavioural and neuronal markers of numerosity zero in carrion crows. Crows were trained on a numerosity discrimination task with small numerosities including the ES. Behavioural performance functions exhibited a numerical distance effect in one crow, suggesting the quantitative handling of empty set alongside countable numerosities. Single-cell recordings in the nidopallium caudolaterale (NCL) revealed a great proportion of neurons tuned to the ES. NCL neurons integrated the empty set in the neural number line, shown by neuronal distance and size effects. Neuronal representations were behaviourally relevant. These findings mark the first account of neuronal ES representations outside the mammalian taxon. They underline the pivotal role of the NCL not only for numerical-, but general cognition.

More than nothing: Behavioural and neuronal correlates of numerosity zero in the carrion crow

Anatomical and cognitive adaptations to overcome morph-mechanical constraints of the vocal folds increase vocal diversity across taxa. The Asian elephants´ vocal repertoire ranges from infrasonic rumbles (F0 ~ 20 Hz) to higher pitched trumpets (F0 340-540 Hz) and species-specific squeaks (F0 300-2300 Hz). While rumbles are congruent with vocal fold vibration in large sized mammals, trumpets and squeaks were hypothesised to be emitted by the trunk without current knowledge of the sound source. We use an acoustic camera to visualise nasal trumpet but oral squeak emission and an event of simultaneous oral and nasal emission (biphonation) in a captive group of female Asian elephants. By combining these findings with acoustic, behavioural and morphological data we suggest that trumpets are produced by vibration of nasal cartilages, but squeaks by vibration of the tensely closed lips. Our data further suggests that context or vocal production learning might be involved in squeak sound production

Sound production of Asian elephant high-frequency vocalisations

Children and adults use linguistic context to learn new words. For instance, in “She wears the dax,” “dax” likely refers to clothing. We asked whether learners retain these constraints across ambiguous word-learning exposures. Adults (n=139) learned 12 words. On Exposure 1, novel nouns were presented as the object of either Restrictive (e.g., “wears”) or Non-restrictive (“finds”) verbs. Participants selected which of two compatible referents the noun referred to. On Exposure 2, participants heard each noun again and chose between a distractor referent and the unselected referent from Exposure 1—now the only referent compatible with the previous Restrictive verb. If adults retain selectional restrictions, then Restrictive verbs should increase selection of the compatible referent. However, we found no difference between Restrictive (M=.74, SD=.26) and Non-restrictive (M=.76, SD=.24) conditions, p=.24. This suggests adults use verbs’ selectional restrictions to identify referents in the moment but do not retain these restrictions across exposures.

New exposure, no constraints: Semantic restrictions on novel nouns do not constrain adults’ subsequent referent selections

Some theories of abstract word representation posit a role for affective information; however, little has been done to delineate how this holds for the class of emotion concepts relative to other types of abstract concepts. Work using distributional semantic models has shown that emotion words tend to co-occur with other highly affective words, complicating the picture of how affective information contributes to the grounding of abstract concepts generally and emotion concepts specifically. Here, a novel set of data from 180 participants collected using a feature generation paradigm with emotion, non-emotion-related abstract, and concrete stimuli is leveraged to test how the distributional properties of emotion concepts and their associated features differs from those of other abstract concepts. Using co-occurrence statistics and normative ratings for affect, results show the importance of affect differs between emotion and non-emotion-related abstract words.

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How do chimpanzees explore their environment prior to a risky decision?

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