Research Overview Current Projects People Publications Facilities Opportunities Training Grant Links Internal Resources

Mark S. Seidenberg
Donald O. Hebb Professor
Hilldale Professor
Psychology and Cognitive Neuroscience

534 Psychology Bldg
University of Wisconsin-Madison
Dept of Psychology (WJ Brogden Hall)
1202 West Johnson Street
Madison, WI 53706-1696

Phone: (608)263-2553
Fax: (608) 262-4029
Professor of Psychology at the University of Wisconsin-Madison
Ph.D., 1980, Columbia University
Brief Bio

Overview of Current Research:

Here's a simple summary of my research:

I study language and reading, with the goal of understanding how these skills are acquired and used, and the brain circuits that support them. The work involves a combination of behavioral studies, neuroimaging, and computational (connectionist) modeling.

Here's what that means:

About Language

There are traditional questions that people ask about language: what do we know when we know language? How is this information acquired? How is this information used in comprehending and producing language? What are the brain structures that support the acquisition and use of language? Why do people acquire language and not other species? How does language relate to other cognitive capacities? What do language disorders due to neuropathology tell us about the language system? Questions such as these have dominated linguistic and psycholinguistic research for many years, ever since Chomsky formulated them in the 1960s.

Our research attempts to advance the understanding of these issues, while challenging many broadly-held assumptions about them. For example, since Chomsky's early work, knowledge of language has been equated with knowing a grammar. Many consequences followed from this initial assumption. For example, if the child's problem is to converge on the grammar of a language, then the problem does seem intractable unless there are innate constraints on the possible forms of grammar. What if we abandon the assumption that knowledge of language is represented as a grammar in favor of, say, neural networks, a more recently developed way of thinking about knowledge representation, learning, and processing? Do the same conclusions about the innateness of linguistic knowledge follow? The answer is: not at all.

Our goal, then, has been to articulate an alternative framework for thinking about the classic questions listed above. This is not easy: traditional grammarians have about a 40 year lead on us, and only a few linguists actually think the alternative approach will succeed. However, it's a very interesting moment in the study of language. For many years the study of language was dominating by theoretical linguistics, particularly syntax. More recently, there have been important insights coming from outside of traditional grammatical theory: from computational modeling, from studies of the brain bases of learning and neurodevelopment, from renewed interest in the statistical properties of language (which were ignored for many years following Chomsky's famous observations about the statistical triviality of sentences such as "Colorless green ideas sleep furiously").

Chomsky and his followers have always had their critics. However, there was never an alternative theory that could explain basic facts, such as how children acquire language under the conditions that they do. I think for the first time we have the major components of such a theory in hand. And they suggest the remarkable possibility that the standard conclusions about the nature of language and how it is acquired are just dead wrong. This would be an incredible turn of events, a major development in the intellectual history of the study of language.

That's why it's an interesting moment to be studying language.

About Reading

My own research focuses on various aspects of language including reading, which is a particular use of language, how reading skill is acquired by children, and forms of dyslexia that occur developmentally or in adults as a consequence of neuropathology. This research involves both behavioral studies and the development of large-scale computational ("neural network") models of normal and disordered language. I am collaborating with researchers at Haskins Labs on neuroimaging studies of beginning and skilled readers, and dyslexics.

Reading is interesting in its own right, but it also provides a domain in which to study general theoretical principles concerning knowledge representation, learning, information processing, and their brain bases. And so the theoretical framework that was originally developed in connection with reading is being applied to many other aspects of language, including phonology, morphology and lexical semantics, and its implications concerning the brain bases of language are beginning to be studied using neuroimaging. At the moment I am very excited about using the neural network approach to look at language acquisition, where it's clear that statistical learning plays a huge role. Both Tim Rogers and I are co-supervising students with Jenny Saffran, one of the world experts in language acquisition and learning in infancy, and we have begun studies that will bring the computational framework together with evidence about how babies learn. We've had a number of exchanges with people in Science and other journals about these issues, which are controversial (see papers in the publication archive). The framework is also being applied to the classic question as to whether there is a critical period for language; see the Seidenberg and Zevin (2006) chapter also in the publications archive.

I am also deeply committed to pursuing the educational implications of reading research. One current focus is on the so-called "achievement gap," which refers to the lower achievement of poor and minority children in school, particularly in areas such as reading. I began work on this topic with the support of a seed grant from the Wisconsin Institutes for Discovery. The research continues under a new "research hub" grant from NICHD to Julie Washington, Nicole Patton-Terry (both at Georgia State University) and myself in late 2012. Our focus is on ways in which language background affects early school achievement. Most African American children speak the dialect termed African American English, whereas the language in the school is some version of "standard" (also called "mainstream") American English. This dialect mismatch has many effects on the African American child's school experience; it makes tasks such as learning to read literally more difficult than for children for whom there is no dialect mismatch. Our studies focus on young children's knowledge of the alternative dialects, factors that affect ability to switch between dialects, and ways that negative effects of the mismatch can be ameliorated. The idea is to provide supplementary language experiences early, when the child's plasticity for language is high. We can also use our computational models of reading to predict where dialect differences will interfere with progress, and how experience can be structured to improve performance.

For details about some of the main current projects, click here.