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LINGUIST List 24.3255

Tue Aug 13 2013

Confs: Neuroling, Psycholing, Cognitive Science/USA

Editor for this issue: Caylen Cole-Hazel <caylenlinguistlist.org>

Date: 10-Aug-2013
From: Heather Simpson <hsimpsonumail.ucsb.edu>
Subject: Cognition and Language Workshop 2013
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Cognition and Language Workshop 2013
Short Title: CLaW

Date: 31-Aug-2013 - 01-Sep-2013
Location: Santa Barbara, CA, USA
Contact: Heather Simpson
Contact Email: hsimpsonumail.ucsb.edu
Meeting URL: http://www.linguistics.ucsb.edu/claw/

Linguistic Field(s): Cognitive Science; Neurolinguistics; Psycholinguistics

Meeting Description:

CLaW is a faculty and graduate student conference on language and cognition, organized by SCUL (Studying the Cognitive Underpinnings of Language), an interdisciplinary research group at the University of California, Santa Barbara.


CLaW will feature 13 talks and 6 poster presentations, as well as a keynote address from Luca Onnis (Associate Professor at University of Hawaii at Manoa) on topics relevant to language and cognition from empirical data driven perspectives. CLaW is organized by SCUL (Studying the Cognitive Underpinnings of Language), an interdisciplinary research group at the University of California, Santa Barbara. See the Announcement Information below for the keynote address abstract.

If you would like to attend, please email claw.ucsbgmail.com to register. There is a $10 registration fee, payable on site.


The schedule for the Cognition and Language Workshop (CLaW) is now available: http://www.linguistics.ucsb.edu/claw/schedule.html

Abstract for Keynote Address:

Language is a complex ability comprised of multiple component skills. A sizable body of research now suggests that language learning and processing could be sub-served by statistical learning (SL) abilities - implicitly tracking distributional relations in sequences of events. Languages contain many probabilistic regularities (for example, a listener who hears ''the'' can predict that a noun will occur after it), so sensitivity to statistical structure in the input can play an important role in mastering language.

The first generation of SL studies provided important proofs of concept' that infants and adults can track statistical relations in miniature artificial grammars, but the arguably simplified nature of these learning scenarios could only offer indirect evidence that the same processes underlie the discovery of a natural language. Recently, however, a series of new studies have established more robust links between SL abilities and language. In addition, this relationship can go both ways, as language experience can modify individual preferences for statistical learning, potentially affecting subsequent learning. I will provide an overview of how corpus analyses, behavioral, and brain imaging methods can be combined to further strengthen our understanding of the underpinnings of statistical language learning.
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