The neural basis of surface dyslexia in semantic dementia
Bibliographic record
Abstract
Semantic dementia (SD) is a neurodegenerative disease characterized by atrophy of anterior temporal regions and progressive loss of semantic memory. SD patients often present with surface dyslexia, a relatively selective impairment in reading low-frequency words with exceptional or atypical spelling-to-sound correspondences. Exception words are typically 'over-regularized' in SD and pronounced as they are spelled (e.g. 'sew' is pronounced as 'sue'). This suggests that in the absence of sufficient item-specific knowledge, exception words are read by relying mainly on subword processes for regular mapping of orthography to phonology. In this study, we investigated the functional anatomy of surface dyslexia in SD using functional magnetic resonance imaging (fMRI) and studied its relationship to structural damage with voxel-based morphometry (VBM). Five SD patients and nine healthy age-matched controls were scanned while they read regular words, exception words and pseudowords in an event-related design. Vocal responses were recorded and revealed that all patients were impaired in reading low-frequency exception words, and made frequent over-regularization errors. Consistent with prior studies, fMRI data revealed that both groups activated a similar basic network of bilateral occipital, motor and premotor regions for reading single words. VBM showed that these regions were not significantly atrophied in SD. In control subjects, a region in the left intraparietal sulcus was activated for reading pseudowords and low-frequency regular words but not exception words, suggesting a role for this area in subword mapping from orthographic to phonological representations. In SD patients only, this inferior parietal region, which was not atrophied, was also activated by reading low-frequency exception words, especially on trials where over-regularization errors occurred. These results suggest that the left intraparietal sulcus is involved in subword reading processes that are differentially recruited in SD when word-specific information is lost. This loss is likely related to degeneration of the anterior temporal lobe, which was severely atrophied in SD. Consistent with this, left mid-fusiform and superior temporal regions that showed reading-related activations in controls were not activated in SD. Taken together, these results suggest that the left inferior parietal region subserves subword orthographic-to-phonological processes that are recruited for exception word reading when retrieval of exceptional, item-specific word forms is impaired by degeneration of the anterior temporal lobe.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".