Abstract:
Comprehension and production deficits associated with
Broca's agrammatism have traditionally received non-converging
generalizations despite having in common the idea that the deficit has a syntactic source. Such a situation seems to suggest that the locus of the problem may not be in the linguistic representation itself but in its dynamic instantiation. Capitalizing on this insight, I present an alternative view whereby the production and comprehension patterns of impairment manifested in the syndrome stem from a unified processing-based source. Crucially, this view is built upon a linguistically-based processing model that takes syntactic representation to be a dynamic manifestation of sentence formation. This analysis and its implications will be discussed in the context not only of theories of cortical distribution of language, given the localizing value of Broca's aphasia agrammatism, but also of theories of language processing and representation.

MEIJIN BRUTTOMESSO:
Effects of Metrical Subdivision on the Continuation, Reproduction, and Perception of Beat Tempo"

JACKIE THOMPSON:
Context Effects in the Tritone Paradox

HAITHAM JENDOUBI:
Effects of Phase-Shifted Subdivisions on Synchronization with a Beat

University of Connecticut

Animal models of early cortical disruption: possible relevance tso higher-order functional disruptions in humans

March 27, 12:30 PM
Haskins

Ken McRae, University of Western Ontario
Psychology Department.

Testing An Attractor Network Model of Word Meaning

Abstract
Over the past several years, we have investigated a number of predictions derived from a distributed attractor network view of word meaning. This view differs substantially from older spreading activation semantic network models. In particular, a theory based on attractor networks entails that people naturally (and implicitly) learn the distributional statistics that are present in their environment, and that this knowledge influences the computation of word meaning. I describe simulations and associated human experiments to make three main points. First, people learn and use information regarding how features of objects are correlated (e.g., things that have four legs also tend to have fur). Second, distinctive features that are strong cues to an object's identity (e.g., if something moos, it's a cow) are computed quickly when people read a concept name (such as "cow"). Third, superordinate concepts such as "fruit" can be learned from experience with basic-level concepts such as "cherry" and "banana" by combining the influence of labeling with knowledge of distributional statistics. Although we use an attractor network model that contains no transparent hierarchical structure, it not only produces emergent behavior that makes it seem as if it has a hierarchical architecture, it also explains data that are inconsistent unless network temporal dynamics are taken into account.

March 28, 4:00PM
UConn
Bousfield 160, STORRS

Ken McRae, University of Western Ontario

How Knowledge of Real-world Events Influences Language Comprehension

Abstract
A significant proportion of everyday utterances concern real-word events. Thus, people's knowledge of everyday events, including their common participants, is an important component of language comprehension. In many theories of language comprehension, event knowledge is outside of "the lexicon", is accessed slowly, and influences comprehension only after an architecturally-determined time delay. In contrast, I present results from semantic priming and sentence comprehension studies that strongly support a view in which event knowledge is organized efficiently so that it is computed immediately from words (and combinations of words). In addition, our studies show that event knowledge is an important source of information that is used to generate expectancies about upcoming concepts and syntactic structure during on-line sentence comprehension.

Abstract:
Variation set structure --- partial alignment of successive utterances in child-directed speech --- has been shown to correlate with progress in the acquisition of syntax by children. The present study demonstrates that arranging a certain proportion of utterances in a training corpus in variation sets facilitates word segmentation and phrase structure learning in the acquisition of miniature artificial languages by adult subjects.

The positive effects of variation sets in the reported experiments suggest that learners can reuse the same learning procedures --- alignment, and comparison --- at different levels of linguistic structure (here, lexical and phrasal units). We are presently extending
our approach to investigate whether variation sets also facilitate the learning of other core features of language, such as lexical categorization, long-distance dependencies, and recursion.

Beyond having implications for understanding the course of L1 acquisition by children, this work contributes to the development of more efficient algorithms for automatic language acquisition, as well as better methods for L2 instruction.

Also visiting will be Albert Zhang and Dan Hudock from East Carolina University. (PowerPoint presentation)

"Hearing lips and seeing voices: How cortical areas supporting speech production mediate audiovisual speech perception."

Len Katz. Two statistical issues journal editors are concerned about:
(1) the appropriate analysis when your experiment includes items or tokens, and
(2) the death of null hypothesis testing.

Fermin Moscoso Del Prado Martin. MRC Cognition and Brain Sciences Unit, Cambridge, UK. A sketch of an information-theoretical approach to lexical processing.