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Language reflects and supports the ability to reason about the likelihood or goodness of unrealized possibilities–a critical capacity underlying practical decisions, scientific explanations, moral judgments, legal agreements, and attitudes like regret and relief. Conditional and modal expressions are ways to talk about what is, will be or would have been likely or preferable, and to flag contingencies and degrees of confidence. In English, such expressions (examples are ‘if-then’ sentences and auxiliaries like ‘must’ and ‘might’) have been extensively studied. However, languages other than English employ radically different ways to express similar notions, and much remains unknown about the cross-linguistic picture with regard to both the variety of expressive means and the uniformity of the underlying concepts. This project works towards filling that gap. Its linguistic goal is to elucidate how general concepts and cognitive abilities interact with the grammatical idiosyncrasies of different languages. Its wider applications include language teaching and artificial intelligence, where the ability to use and understand modals and conditionals correctly helps improve the quality of machine translation systems and human-computer interfaces.

This project is funded by:

National Science Foundation: #2116972, "Research on conditional and modal language" (M. Kaufmann, PI; S. Kaufmann, Co-PI), 2021-23.
UConn College of Arts and Sciences Research in Academic Themes grant, "Conditional Thought and Talk" (Mitch Green, Magda Kaufmann, Stefan Kaufmann), 2022-23.

Teruyuki Mizuno: PhD defense
Teruyuki Mizuno will defend his dissertation “Counterfactual expressions: an investigation into their structures and meanings” on February 16, 2023. Major Advisor: Stefan Kaufmann Associate Advisors: Jon Gajewski, Magdalena Kaufmann

Stefan Kaufmann: UCHI fellow’s talk
Stefan Kaufmann presented his work on “Talking about time and possibility” as a fellow’s talk at the UConn Humanities Institute on February 1, 2023.

Muyi Yang: PhD Defense
Muyi Yang will defend her dissertation “Varieties of conditionals as definite descriptions” on December 15, 2022. Major Advisor: Magdalena Kaufmann Associate Advisors: Jon Gajewski, Stefan Kaufmann

E-mail:	magdalena.kaufmann@uconn.edu stefan.kaufmann@uconn.edu
Address:	Department of Linguistics Oak Hall, Room 368 365 Fairfield Way, Unit 1145 Storrs, CT 06269-1145

2/10 Logic Colloquium: Eugenio Orlandelli (Bologna)

Logic Colloquium: Eugenio Orlandelli (Bologna)

Friday, February 10th, 2023

02:00 PM - 03:30 PM

Storrs Campus
Zoom

Join us in the Logic Colloquium!

Eugenio Orlandelli (Bologna)

Quantified modal logics: One approach to rule them all!

We present a general approach to quantified modal logics (QML) that can simulate most other approaches. The language is based on operators indexed by terms which allow to express de re modalities and to control the interaction of modalities with the first-order machinery and with non-rigid designators. The semantics is based on a primitive counterpart relation holding between n-tuples of objects inhabiting possible worlds. This allows an object to be represented by one, many or no object in an accessible world. Moreover by taking as primitive a relation between n-tuples we avoid the shortcomings of standard individual counterparts. Finally, we use cut-free labelled sequent calculi to give a proof-theoretic characterisation of the quantified extensions of each first-order definable propositional modal logic. In this way we show how to complete many axiomatically incomplete QML.

https://logic.uconn.edu/calendar/

Contact Information: logic@uconn.edu
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2/10 ECOM Speaker Series: Alison Springle

ECOM Speaker Series: Alison Springle

Friday, February 10th, 2023

04:00 PM - 05:00 PM

Storrs Campus
FSB220

ECOM Speaker Series will host Alison Springle (Oklahoma University, Philosophy). The title of her talk is "Radicalizing Practical Representations." The event will be held in Family Studies 220, and will be broadcasted via Zoom. For details, contact aliyar.ozercan@uconn.edu

Contact Information: aliyar.ozercan@uconn.edu
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2/17 Linguistics Colloquium: Robert Stalnaker (MIT)

Linguistics Colloquium: Robert Stalnaker (MIT)

Friday, February 17th, 2023

04:00 PM - 06:00 PM

Storrs Campus, Storrs Campus
Oak Hall

Join us in the Logic Colloquium for a talk by Robert Stalnaker!

Contact Information: chui_yi.lee@uconn.edu; zixi.liu@uconn.edu
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2/24 Logic Colloquium: Elitzur Bar-Asher Siegal

Logic Colloquium: Elitzur Bar-Asher Siegal

Friday, February 24th, 2023

02:00 PM - 03:30 PM

Storrs Campus, Storrs Campus
BUSN 218 & Zoom

Join us for a talk in the Logic Colloquium by Elitzur Bar-Asher Siegal (Jerusalem)!

Details t.b.a.

https://logic.uconn.edu/calendar/

Contact Information: logic@uconn.edu
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2/24 CogSci Colloquium: Thomas Naselaris

CogSci Colloquium: Thomas Naselaris

Friday, February 24th, 2023

04:00 PM - 05:30 PM

Storrs Campus
Oak Hall Room 117

Speaker: Dr. Thomas Naselaris, an Associate Professor from Department of Neuroscience at the University of Minnesota.

Time & Location: 4PM, Friday February 24th, 2023, in Oak Hall Room 117. Please RSVP on the COGS colloquium page.

Talk Title: “Why Do We Have Mental Images?”

Abstract: Everyone who experiences mental imagery is the world expert on the contents of their own mental images. We argue that this privileged perspective on one’s own mental images provides very limited understanding about the function of mental imagery, which can only be understood by proposing and testing hypotheses about the computational work that mental images do. We propose that mental imagery functions as a useful form of inference that is conditioned on visual beliefs. We implement this form of inference in a simple generative model of natural scenes, and show that it makes testable predictions about differences in tuning to seen and imagined features. We confirm these predictions with a large-scale fMRI experiment in which human brain activity was sampled while subjects generated hundreds of mental images. We speculate that ongoing mental imagery may impact the structure of noise correlations in the visual system, and present a preliminary analysis of the Natural Scenes Dataset that appears to be consistent with these speculations.
Bio: Thomas is an Associate Professor in the Department of Neuroscience at the University of Minnesota, and a member of the Medical Discovery Team on Optical Imaging and Brain Science at the Center for Magnetic Resonance Research. He is co-founder and currently Executive Chair of the Conference on Cognitive Computational Neuroscience.

Contact Information: crystal.mills@uconn.edu
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