My work pictured by AI – Kinkini Bhadra

What is this work about? The neural underpinnings of semantic representations involve a distributed network of cortical regions that integrate multimodal information relating to concepts. These semantic representations are formed dynamically through novel experience and information, including linguistic. Most models of semantic knowledge and its structure in the brain have been based on western monolingual populations that fail to capture the rich and diverse multilingual experience that is the reality for a majority of the global population. In multilingual speakers, a given concept is represented by multiple labels, with each label comprising its own phonological and lexico-semantic connections between and within languages. Moreover, evidence from linguistics and cognitive science suggest behavioral and physiological cross-linguistic differences in several conceptual domains and their respective boundaries, including colors, household containers, motion events and odors. Therefore, in the multilingual speaker, increased inter-language connections at phonological, lexico-semantic and conceptual levels may interact with language-specific properties inherent to word meaning and subsequent categorization (i.e., lexico-semantic features), altering the relevance of certain properties of the concept itself and its relational association to other concepts. Whether this alteration leads to differences in the quantity and quality of semantic representations and their associations in multilinguals of typologically-distinct versus typologically-similar languages is unclear and forms the central question of this thesis; implications of these findings may extend to patients with semantic dementia, a language-related neurodegenerative disease which destroys conceptual knowledge overtime.

The first word that came to mind when seeing the AI-generated picture? Eclecticism.

What is this work about? Joint actions require various coordination mechanisms in order to achieve a successful joint outcome. To understand how joint action evolved in humans, research requires a comparative approach by investigating whether other animals have similar motoric and mental coordination skills that would facilitate their joint actions. Common marmosets are cooperative breeders, just like humans, and thus their parental care system forms an ideal model to further investigate the different proximate mechanisms of joint action. This study focusses on infant transfers in marmosets, a highly important and risky joint action, for which both parents are required to coordinate efficiently. How marmosets exactly achieve a successful transfer, and what the relevant traits are, is unknown. To this end, we analyzed motor coordination during transfers, including micro-analyses of coordination signals such as touch and mutual gaze between parents. All our data was collected in captive housing as first stage of this project and we are developing a protocol for research in the field, to further understand how ecological conditions impact this behavior.

The first word that came to mind when seeing the AI-generated picture? Alliance.

What is this work about? This paper talks about a new way of thinking about how children learn to communicate. The idea is that when kids have different kinds of experiences talking with others, it affects how they communicate in the future. If they have lots of experiences where talking doesn’t work well, they will learn to use more ways to communicate and be more flexible when they talk. The authors use bilingual children as an example to explain this idea. They talk about how growing up with two languages affects how kids learn to communicate. Children who speak only one language and those who speak two or more languages communicate differently. Children who speak two languages are better at understanding what their communication partner is trying to say. They also adapt more easily to what the other person needs and use gestures to explain things more often. They are better at fixing misunderstandings and responding in a way that makes sense. The general idea is, however, not limited to bilingual communication but can also be applied to other challenge communicative situations.

The first word that came to mind when seeing the AI-generated picture? Confused.