learning

Presentation at CNS symposium on “Prediction, adaptation and plasticity of language processing in the adult brain”

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Earlier this week, Dave Kleinschmidt and I gave a presentation as part of a mini-symposium at Cognitive Neuroscience Conference  on “Prediction, adaptation and plasticity of language processing in the adult brain” organized by Gina Kuperberg.  For this symposium we were tasked to address the following questions:

  1. What is prediction and why do we predict?
  2. What is adaptation and why do we adapt?
  3. How do prediction and adaptation relate?

Although we address these questions in the context of language processing, most of our points are pretty general. We aim to provide intuitions about the notions of distribution, prediction, distributional/statistical learning and adaptation. We walked through examples of belief-updating, intentionally keeping our presentation math-free. Perhaps some of the slides are of interest to some of you, so I attached them below. A more in-depth treatment of these questions is also provided in Kleinschmidt & Jaeger (under review, available on request).

Comments welcome. (sorry – some of the slides look strange after importing them and all the animations got lost but I think they are all readable).

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It was great to see these notions discussed and related to ERP, MEG, and fMRI research in the three other presentations of the symposium by Matt Davis, Kara Federmeier and Eddy Wlotko, and Gina Kuperberg. You can read their abstracts following the link to the symposium I included above.

Perspective paper on second (and third and …) language learning as hierarchical inference

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We’ve just submitted a perspective paper on second (and third and …) language learning as hierarchical inference that I hope might be of interest to some of you (feedback welcome).

multilingualism
Figure 1: Just as the implicit knowledge about different speakers and groups of speakers (such as dialects or accents) contains hierarchical relations across different language models, the implicit knowledge about multiple languages can be construed as a hierarchical inference process.

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congratulations to Ting Qian and Dave Kleinschmidt

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Congratulations to Ting Qian and Dave Kleinschmidt, both students in the Brain and Cognitive Science Program at Rochester and members of HLP Lab, for being awarded a Google Travel Grant to CogSci 2012 in Sapporo, Japan, where they will present their work. which centers around implicit statistical learning and adaptation during language acquisition and processing:

And, thank you, dear Google.