This paper describes a novel theoretical framework of how the position of a letter within a string is encoded, the SERIOL model (sequential encoding regulated by inputs to oscillations within letter units). Letter order is represented by a temporal activation pattern across letter units, as is consistent with current theories of information coding based on the precise timing of neural spikes. The framework specifies how this pattern is invoked via an activation gradient that interacts with subthreshold oscillations and how it is decoded via contextual units that activate word units. Using mathematical modeling, this theoretical framework is shown to account for the experimental data from a wide variety of string-processing studies, including hemispheric asymmetries, the optimal viewing position, and positional priming effects

similarity effects in masked associative priming One issue that all models of visual word recognition in alphabetic orthographies must ultimately take a position on is how the human processing system encodes letter positions when creating internal orthographic representations. Furthermore, although the choice of a coding scheme might seem to be a secondary aspect of these models, it can have a large impact on a model’s predictions (Andrews, 1996). For example, virtually all of the current models assume that the derived orthographic representation activates the lexical representations of formally similar words

A letter in the peripheral visual field is much harder to identify in the presence of nearby letters. This is called "crowding". In general, masking is a procedure: introducing any "mask" pattern that affects discriminability of the signal. Crowding conforms to the masking paradigm, but the crowding effect is unlike ordinary masking. Here we characterize crowding, and present diagnostic tests that distinguish it from ordinary masking. In ordinary masking, the signal disappears. In crowding, it remains visible, but is ambiguous, confounded with its neighbors. Masks are usually effective only if they overlap the signal, but the crowding effect extends over a large region. The width of that region is proportional to signal eccentricity from the fovea and independent of signal size, mask size, signal and mask font, and number of masks. At 4 deg eccentricity, the threshold contrast for identification of a 0.32 deg signal letter is elevated (up to six-fold) by mask letters anywhere in a 2.3 deg region, seven times wider than the signal. In ordinary masking, threshold contrast rises as a power function of mask contrast, with a shallow log-log slope of 0.5 to 1, while in crowding, threshold is a sigmoidal function of mask contrast, with a steep log-log slope of 2 at close spacing. Most remarkably, although the threshold elevation decreases exponentially with spacing, the threshold and saturation contrasts of crowding are independent of spacing. Finally, ordinary masking is similar for detection and identification, but crowding occurs only for identification, not detection. More precisely, crowding occurs only in tasks that cannot be done based on a single detection by coarsely coded feature detectors. These results (and observers' introspections) suggest that ordinary masking b...

This article focuses on applying the SERIOL model of orthographic processing to dyslexia. The model is extended to include a phonological route and reading acquisition. We propose that the temporal alignment of serial orthographic and phonological representations is a key aspect of learning to read, driving the formation of a phonemic encoding. The phonemic encoding and the serial representations are mutually reinforcing, leading to automatic, proficient processing of letter strings. A breakdown in any component of this system leads to the failure to form stringspecific phonological and visual representations, resulting in impaired reading ability. Following the pioneering work of Liberman and colleagues (1974), research into dyslexia has focused on phonological deficits. As discussed by Castles and Colheart (2004), there is a wide range of evidence that dyslexics are impaired in phonological awareness tasks, such as phoneme deletion, phoneme counting and phoneme lending. This correlation has largely been taken to reflect causality. That is, impaired phonological awareness is thought to reflect abnormal phonological representations, which are thought to be the fundamental cause of dyslexia. However, a causal relationship between phonological awareness and

The de�nition of orthographic neighbour (Coltheart et al., 1977) was analysed in two experiments using a variety of the three-�eld technique (Humphreys et al., 1988). With this technique, a clearly visible prime (in lower-case letters) is followed by a brie�y presented upper-case word which is immediately masked. Pairs of �ve-letter neighbouring words were selected. Only orthographically related pairs that differed from the prime by the third letter (women– WOVEN) or the fourth letter (frost–FRONT) showed (inhibitory) relatedness effects compared with an unrelated word condition. The results suggest that models of visual word recognition should be modi�ed to address the fact that some letter positions are more important than others.

Recent research has shown that letter identity and letter position are not integral perceptual dimensions (e.g., jugde primes judge in word-recognition experiments). Most comprehensive computational models of visual word recognition (e.g., the interactive activation model, J. L. McClelland & D. E. Rumelhart, 1981, and its successors) assume that the position of each letter within a word is perfectly encoded. Thus, these models are unable to explain the presence of effects of letter transposition (trial–trail), letter migration (beard–bread), repeated letters (moose–mouse), or subset/superset effects (faulty–faculty). The authors extend R. Ratcliff’s (1981) theory of order relations for encoding of letter positions and show that the model can successfully deal with these effects. The basic assumption is that letters in the visual stimulus have distributions over positions so that the representation of one letter will extend into adjacent letter positions. To test the model, the authors conducted a series of forced-choice perceptual identification experiments. The overlap model produced very good fits to the empirical data, and even a simplified 2-parameter model was capable of producing fits for 104 observed data points with a correlation coefficient of.91.

Dividing attention across multiple words occasionally results in misidentifications whereby letters apparently migrate between words. Previous studies have found that letter migrations preserve withinword letter position, which has been interpreted as support for position-specific letter coding. To investigate this issue, the authors used word pairs like STEP and SOAP, in which a letter in 1 word could migrate to an adjacent letter in another word to form an illusory word (STOP). Three experiments show that both same-position and adjacent-position letter migrations can occur, as well as migrations that cross 2 letter positions. These results argue against position-specific letter coding schemes used in many computational models of reading, and they provide support for coding schemes based on relative rather than absolute letter position. A key issue that must be addressed in any theory of visual word recognition is how to code for letter position: Without coding of position, it is not possible to distinguish anagrams like CAT and ACT. Although relatively little empirical work has been directed at assessing the relative merits of different letter coding schemes, the choice of coding scheme plays a central role in the performance of

Five theories of how letter position is coded are contrasted: position-specific slot-coding, Wickelcoding, open-bigram coding (discrete and continuous), and spatial coding. These theories make different predictions regarding the relative similarity of three different types of pairs of letter strings: substitution neighbors, neighbors-once-removed, and double-substitution neighbors. In Experiment 1, we used an illusory word paradigm and found that neighbor-once-removed similarity contexts resulted in fewer illusory word reports than substitution neighbors but more illusory words than double-substitution neighbors. In Experiments 2 and 3, we used a masked form priming technique with a lexical-decision task. The pattern of facilitation was as predicted by spatial coding but was incompatible with slot-coding, Wickelcoding, and both versions of open-bigram coding. These results provide further support for the SOLAR (self-organizing lexical aquisition and recognition) model of visual word identification.

The processing advantage for words in the right visual field (RVF) has often been assigned to parallel orthographic analysis by the left hemisphere and sequential by the right. The authors investigated this notion using the Reicher-Wheeler task to suppress influences of guesswork and an eye-tracker to ensure central fixation. RVF advantages obtained for all serial positions and identical U-shaped serial-position curves obtained for both visual fields (Experiments 1-4). These findings were not influenced by lexical constraint (Experiment 2) and were obtained with masked and nonmasked displays (Experiment 3). Moreover, words and nonwords produced similar serial-position effects in each field, but only RVF stimuli produced a word-nonword effect (Experiment 4). These findings support the notion that left-hemisphere function underlies the RVF advantage but not the notion that each hemisphere uses a different mode of orthographic analysis. A considerable amount of evidence indicates that, for most people, language recognition is predominantly a function of neurological systems located in the left cerebral hemisphere. The evidence for this view came initially from studies of the consequences of traumatic and stroke-linked brain damage. However,

We argue that the projection of the visual field to the cortex constrains and informs the modeling of visual word recognition. On the basis of anatomical and psychological evidence, we claim that the higher-level cognition involved in word recognition does not completely transcend initial foveal splitting. We present a schematic connectionist model of word recognition that instantiates the precise splitting of the visual field and the contralateral projection of the two hemifields. We explore the special nature of the exterior (i.e., first and last) letters of words in reading. The model produces the correct behavior spontaneously and robustly. We analyze this behavior of the model with respect to words and random patterns and conclude that the systematic division of the visual input has predictable, general informational consequences and is chiefly responsible for the exterior letters effect. 1