United States

This study investigated the empathy of humans toward non-biological agents like robots and compared it to their empathy toward their conspecifics. 90 participants watched a human and a robot in painful scenarios (32 short videos created with animation techniques) and rated the intensity of pain experienced by the agent. The scenarios were created by manipulating the type of agent experiencing pain (human or robot), the source of pain (object or person), and the type of pain (physical or emotional). Results showed that humans were perceived to feel more pain than robots. In addition, the perceived pain scores were higher for scenarios where the source of pain was an object compared to a person, however, this depended on the type of pain. Emotional pain scores showed significant differences between the source of pain being an object versus a person, but physical pain scores did not depend on the source of pain.

CogSci 2023

Perceived pain of humans and robots: An exploration of the effect of agent, pain source, and pain type in pain attribution to biological and non-biological agents

Colleagues and Friends:

I am very happy to welcome you to the 14th annual Canadian Neuroscience Meeting, and to the first virtual edition of our meeting. I want to highlight the important work the CAN meeting chair, **Roger Thompson** and co-chair, **Alyson Fournier**, did to put together the great program we are offering this year. Moving to a virtual format required a complete re-design of the program, and both Roger and Alyson did a splendid job in providing us with an appealing and well adapted program for our first virtual event. I wish to thank them for this very important effort.

Highlights of this year’s scientific meeting include invited speakers **Michael Hausser, Franck Polleux, Gwyneth Card, Magdalena Götz**and Brain Prize winner **Huda Zoghbi**. Plenary and parallel symposia, proposed by our members complete our diverse [scientific program.](https://can-acn.org/meeting-2021/program-2021/)

The 2021 Advocacy session, chaired and organized by CAN advocacy committee chair **Karun Singh**, will feature a special lecture and question period with Member of Parliament and past Science Minister **Kirsty Duncan**. This will be followed by a short overview of CAN’s advocacy activities over the last year. We invite you to participate in this session for insight from Dr. Duncan on the workings of Parliament Hill, and to learn more about what CAN has been doing to promote neuroscience research in Canada.

We are also excited to host **Lisa Willis** in the Equity Diversity and Inclusion session, organized by EDI committee chair **Jibran Khokhar**.

A special highlight of our meeting will be the lectures by award-winning young neuroscientists. We are please to host the CAN 2020 Young Investigator Award winner **Mihaela Iordanova**, and CAN 2021 Young Investigator Award winners **Aaron Phillips** and **Tabrez Siddiqui**. Highlights will also include presentation by the top three winners of the CAN-CIHR-INMHA Brain Star Award winners, **Claire Gizowski, Nuria Daviu Abant** and **Lukas Tamayo-Orrego**.

Independently organized satellite symposia complement and complete this exciting program, check them out here: https://can-acn.org/meeting-2021/2021-satellite-symposia/

Some of the most engaging sessions are always the poster sessions featuring the work of our trainees, so make sure to log in to Gather Town during the poster sessions to chat with the presenters.
We hope you enjoy this program, and look forward to welcoming you, virtually.

Shernaz Bamji

President of the Canadian Association for Neuroscience

![](https://assets.underline.io/uploads/markdown_image/1/image/b9aea25343a87d5aac3b9367dc780974.jpg)



Please head to https://can-acn.org/meeting-2021/registration-2021/ to register. 

CAN-ACN 2021

14th Canadian Neuroscience Meeting from August 23rd-25th

poster

The 45th Annual Meeting of the Cognitive Science Society will take place in Sydney, Australia as a modified hybrid conference. Presentations from the main-session room will be live-streamed every day for all events. This will include all invited talks and award sessions. Recordings of all CogSci 2023 sessions will be made available for on-demand viewing after the conference.<br>
The in-person component will be held at the International Convention Centre Sydney at Darling Harbour. The Conference will take place Wednesday July 26th – Saturday July 29th, 2023 (Wednesday, July 26th is the Workshops Day).

Join us!

<br>[**The Program at a Glance can be found here**](https://cognitivesciencesociety.org/wp-content/uploads/2023/07/COgSci-PAAG-V2.pdf)
<br>[**The Detailed Program can be found here**](https://online.fliphtml5.com/ebtyf/mswz/)
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#### **CogSci 2023 Program Book**
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The 45th Annual Meeting of the Cognitive Science Society presents the latest research across cognitive science and highlights the theme of Cognition in Context.

In early stages of language acquisition, children often make inflectional errors on regular verbs. For example, Spanish-speaking children produce –a (present-tense 3rd person singular) when other inflections are expected. Most previous models of morphology learning have focused on later stages of learning relating to production of irregular verbs. We propose a computational model of Spanish inflection learning to examine the earlier stages of learning and present a novel data set of gold-standard inflectional annotations for Spanish verbs. Our model replicates data from Spanish-learning children, capturing the acquisition order of different inflections and correctly predicting the substitution errors they make. Analyses show that the learning trajectory can be explained as a result of the gradual acquisition of inflection-meaning associations. Ours is the first computational model to provide an explanation for this acquisition trajectory in Spanish, and represents a theoretical advance more generally in explaining substitution errors in early morphology learning.

Modeling Substitution Errors in Spanish Morphology Learning

Understanding how children process ambiguous words is a challenge because sense disambiguation depends on sentence context bottom-up and top-down aspects. Here, we seek insight into this phenomenon by investigating how such a competence might arise in large distributional learners (Transformers) that purport to acquire sense representations from language input in a largely unsupervised fashion. We investigated how sense disambiguation might be achieved using model representations derived from naturalistic child-directed speech. We tested a large pool of Transformer models, varying in their pretraining input size/nature as well as the size of their parameter space. Tested across three behavioral experiments from the developmental literature, we found that these models capture some essential properties of child sense disambiguation, although most still struggle in the more challenging tasks with contrastive cues. We discuss implications for both theories of word learning and for using Transformers to capture child language processing.

Modeling Children's Word Sense Disambiguation with Large Language Models: Insights and Challenges

Artificial grammar learning (AGL) experiments are commonly used to assess implicit learning. However, in these tasks participants may acquire explicit rather than implicit knowledge. We combined an AGL task with measures of metacognition to assess whether participants acquired explicit knowledge of the grammar. Participants were initially exposed to sequences of visual symbols generated by an artificial grammar, followed by a testing phase in which they classified sequences as either grammatical or ungrammatical. On a subset of trials (choice trials) participants were given the option to either take or skip this classification. If participants had explicit knowledge of the grammar, they should be more likely to take trials when they are confident and skip when they are not. Participants learned the grammar, and performed better in choice trials than in forced trials, demonstrating explicit knowledge of the grammar. These results suggest that AGL paradigms might elicit explicit rather than implicit learning.

Using measures of metacognition to assess the acquisition of implicit and explicit knowledge in artificial grammar learning tasks

Morphosyntactic rules are central to compositional structure in language, and therefore crucial in language acquisition. Previous research on L1 and L2 acquisition suggests that active production leads learners to notice linguistic generalisations more than passive learning does. Here, we explore whether production helps learners to access less obvious generalisations when more than one analysis is possible. We taught participants an artificial language compatible with two grammatical analyses: one that marks semantic roles using word order, the other using case suffixes. After training, half of the participants do a comprehension task, and the other half do a production task. We predict that the comprehension group will adopt the English-like word order analysis, while the production group will be more likely to learn the recurring case suffixes and thus adopt the alternative analysis. Overall, our results shed light on the role of retrieval and production for the acquisition of morphosyntactic generalisations.

Does production facilitate learning morphosyntactic generalisations?

Previous studies suggest that speech categorization is established during the first year of life (Werker & Tees, 1984). However, recent work suggests protracted development through adolescence (McMurray et al., 2018). While the early development has been thought to be driven by the statistical properties of the input, it is unclear if this late phase is also input driven. We asked whether being exposed to diverse linguistic input leads to different patterns of speech categorization. Visual Analogue Scaling task and social network questionnaires were used to measure speech categorization and the effects of linguistic diversity in children’s and adults’ social environments. Results suggest that the development of speech perception is not finished during the first year of life. It continues to be shaped by the developmental changes across the lifespan (McMurray et al., 2018). Importantly, diverse linguistic experience makes both children and adults more flexible in their speech categorization.

Network Diversity Leads to More Flexibility in Speech Categorization

Language learning emerges from dynamic communicative exchanges characterized by two key dimensions. First, children are not simply passive observers, but instead actively seek new information. Second, caregivers scaffold the learning environment. We will present results from a preregistered study (target N=90; 36-72 mos; preregistration: https://osf.io/s24eb/?view_only=7cbed0ef12354103b5fe7a897d13f694; current sample size: N=51) investigating how caregiver scaffolding and children’s information-seeking mutually contribute to word learning. We introduce a novel word learning paradigm that independently varies whether children and/or their caregivers can structure input in a joint Learning Phase and measure children’s word learning in a pre-post test design. We predict that (1) children and caregivers will actively structure learning events and (2) children will benefit when they themselves and their caregivers can structure the Learning Phase. Our results will provide insight into how children’s information-seeking strategies interact with caregivers’ scaffolding to create informative word learning moments.

The dynamics of child-driven active information-seeking and caregiver scaffolding during word learning

The early moments of compound and pseudocompound visual word recognition were investigated by probing their “constituent” concepts (e.g., BED in bedroom and CAP in capsize). This was achieved by concomitantly presenting target words in one visual field (left or right, projected to the right or left hemisphere, respectively) and a picture representing the referent of either the first or second “constituent” in the opposing visual field. The stimuli were presented for 133 ms followed by a backward mask and participants judged whether the word and picture were related to each other. The experimental manipulations consisted of target word type (compound or pseudocompound), word complexity (whole word or “constituent”), probed constituent position (first or second “constituent”), and word projection (left or right hemisphere). Our results suggest that the “constituents” of compounds and pseudocompounds are conceptually accessed. We discuss the implications of our findings for the nature of the visual word recognition system.

Semantic access to constituents of compounds and pseudocompounds: Evidence from dichoptic presentation

In this study we investigate semantic retrieval strategies in order to inform discussions about cognitive mechanisms underlying divergent thinking and creativity. Relying on a verbal fluency task, we map the particular associative strategies participants engage and how they predict their performance. The study starts from the assumption that during divergent thinking processes, participants move along a path through a semantic space, and that each step is prompted by an associative strategy taking them from one word to the next. There are, however, a number of such strategies, and we predict that the outcome of the process is contingent on participants’ engagement of and shift between strategies. The study consists of a two-part elicitation paradigm where participants first conduct a verbal fluency task and then are guided through a meta-cognitive retrieval process to individuate the strategies employed in the task. We report significant correlations between the engagement of associative strategies and outcome measures of divergent thinking in terms of originality, flexibility and fluency.

Semantic Retrieval Strategies in Divergent Thinking

Young children’s intuitions about the meanings of novel nouns reveal foundational biases in language learning, such as biases to generalize nouns to objects of the same shapes, to whole—as opposed to parts of—objects, and to objects from the same taxonomic category. Nevertheless, existing work on such word-learning biases has focused primarily on only one spatial domain to which nouns might refer: objects. In a noun-extension task, we evaluate young children’s and adults’ word-learning biases across two spatial domains—objects and places—and show that young children and adults preferentially extend novel nouns to objects, not the places that the objects are situated in.

Young Children and Adults Extend Novel Nouns to Objects not Places

Systems of semantic categories vary across languages, and it has been proposed that this variation is constrained by a need for efficiency in communication. An important element of efficiency is communicative need, or how often a particular object needs to be referenced. Previous work has sometimes assumed for simplicity that the distribution of need over objects in a semantic domain does not vary across languages or cultures. Here, we explore culture-specific need as it relates to the kinship terminologies of Hindi and English. We assess the efficiency of each language's kin naming system under a variety of need distributions, including one based on that language's usage statistics, one based on the other language's usage statistics, and random permutations of each of those two distributions. Our results suggest that kinship terminologies reflect culture-specific communicative need.

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Modeling Substitution Errors in Spanish Morphology Learning

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