Grapheme-to-lexeme feedback in the spelling system: Evidence from a dysgraphic patient

Abstract

This article presents an argument for grapheme-to-lexeme feedback in the cognitive spelling system, based on the impaired spelling performance of dysgraphic patient CM. The argument relates two features of CM's spelling. First, letters from prior spelling responses intrude into subsequent responses at rates far greater than expected by chance. This letter persistence effect arises at a level of abstract grapheme representations, and apparently results from abnormal persistence of activation. Second, CM makes many formal lexical errors (e.g., carpet → compute). Analyses revealed that a large proportion of these errors are “true” lexical errors originating in lexical selection, rather than “chance” lexical errors that happen by chance to take the form of words. Additional analyses demonstrated that CM's true lexical errors exhibit the letter persistence effect. We argue that this finding can be understood only within a functional architecture in which activation from the grapheme level feeds back to the lexeme level, thereby influencing lexical selection.

Acknowledgments

This study was supported in part by NIH grant NS22201 and NIMH grant R29MH55758. We thank Donna Aliminosa for testing patient CM, and Marie-Josèphe Tainturier for helpful comments on the manuscript.

Notes

Cohen and Dehaene (1998) have suggested that perseverations may arise from normal persistence of activation, when a level of representation receives weaker-than-normal input from other levels. From this perspective, CM's letter intrusions might be interpreted by assuming not that grapheme activation persists to an abnormal extent, but rather that signals from the lexeme level to the grapheme level are abnormally weak, with the result that grapheme activation persisting normally from prior responses has a greater-than-normal influence on grapheme selection for the current response. However, the distinction between abnormally strong grapheme persistence and abnormally weak input from the lexeme level is not relevant for our purposes in this paper. The relevant assumption, made by both interpretations, is that persisting grapheme activation from prior responses is abnormally strong relative to input from the lexeme level. For convenience, we will therefore continue to describe CM's deficit as one of abnormally persisting grapheme activation.

Even though the letters in whole-word perseverative responses are by definition present in preceding responses, these letters were excluded from tabulations of letter intrusions in letter persistence analyses, because the processes leading to whole-response perseverations may not be the same as those leading to persistence of individual letters. This conservative decision avoids the possibility of inflating estimates of the magnitude of the letter persistence effect by including errors that may not involve persistence of individual letters.

The number of intrusion errors in this analysis was 2960 rather than 3174 (the total number of intrusions) largely because errors occurring in the first five trials of each test list were excluded, as described above. A small number of additional errors were excluded because for these errors no control items were available for the analysis described below, which estimated the probability of an intruded letter being present by chance in preceding responses.

The mean number of available control items for a source item was 20.3. On each repetition of the analysis for each source position (E-1, E-2, …) a control item was sampled for each of the approximately 3000 intrusion errors. As a consequence the number of possible control item samples was astronomically large: An average of approximately 20 options were available for each of approximately 3000 choices. (An attempt to calculate the exact number of possible samples in Excel failed due to overflow errors when the value reached approximately 4 × 10³⁰⁷.) Hence, in carrying out 1,000,000 repetitions of the analysis we were not simply generating the same control-item samples repeatedly.

The magnitude of the persistence effect (i.e., the difference between observed and chance rates) was somewhat smaller in the Response-not-Stimulus analysis than in the original analysis that considered all letters in CM's responses. This result is exactly as expected, given that some of CM's letter intrusions were presumably caused by persisting activation of representations for letters that were present on preceding trials in both the correct spelling and in CM's response. For these intrusions the Response-not-Stimulus analysis would not have found the intruded letter among letters present in the response but not in the stimulus on the preceding trial. As a result, we would expect the persistence effect to be smaller in the Response-not-Stimulus analysis than in the main analysis considering all letters in preceding responses.

Orthographic acceptability judgments were made by a computer program that assessed whether each candidate substitution error could be parsed into a sequence of one or more orthographically acceptable syllables. Acceptable syllables were those with an orthographically acceptable nucleus, and (optionally) an acceptable onset and coda.

Although the notion of an attractor network is often associated with the assumption of distributed representations, this association is by no means necessary. Systems with either local or distributed representations for lexemes and graphemes can have an attractor architecture. Although our figures show lexemes and graphemes as individual nodes, our hypothesis is neutral with respect to whether the representations are local or distributed.