1. Embodied letter and word recognition Pieter de Vries University of Groningen

2. Models of visual word processing Interactive Activation Networks (McClelland & Rumelhart, O’Reilly) Bigram Networks (Grainger, Whitney) Models representing serial order as relative activation levels in nodes (Whitney, Davis)

3. A D C B

4. A C1C2 B Binding on the basis of context: nodes C1 and C2 represent the context necessary for the binding of nodes A and B.

5. Binding of location and identity Stimulus A B B A ‘ spatial map’ A B A B LR LR

7. W ORK WORK Specific network structures

8. Role of first and last letter

9. ###### 4= #WORK# 1500 ms. #____# 30 ms. 2000 ms. Letter Reproduction Task

10. Columns give the mean accuracy over subjects, with error bars for 2 standard errors around the mean; Exp. 1: N=12 Exp. 2: N=14 Exp.3: N=22 Triangles give the mean accuracy produced by 100 simulation runs of the model Three experiments on letter reproduction

11. Conclusion Neural binding allows for the adequate representation of letter position in bottom- up and top-down-processing As a result letter and word recognition become embodied