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Towards a computational model of Dyslexia
BMC Neuroscience volume 16, Article number: O12 (2015)
Dyslexics are diagnosed for their poor reading skills. Yet, they characteristically also suffer from poor verbal memory, and often from poor auditory skills. We now hypothesize that dyslexia can be understood computationally as a deficit in integrating prior information with noisy observations. To test this hypothesis we analyzed performance in two tones pitch discrimination task using a two-parameter computational model. One parameter captures the internal noise in representing the current event and the other captures the impact of recently acquired prior information . We found that dyslexics' perceptual deficit can be accounted for by inadequate adjustment of these components: low weighting of their implicit memory in relation to their internal noise (Figure 1). Using ERP measurements we found evidence for dyslexics' deficient automatic integration of experiment's statistics (Figure 2). Taken together, these results suggest that dyslexia can be understood as a well-defined computational deficit.
Raviv O, Ahissar M, Loewenstein Y: How recent history affects perception: the normative approach and its heuristic approximation. PLoS Comput Biol. 2012, 8: e1002731-
This work was supported by Israel Science Foundation (grant no. 616/11).
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Jaffe-Dax, S., Raviv, O., Jacoby, N. et al. Towards a computational model of Dyslexia. BMC Neurosci 16 (Suppl 1), O12 (2015). https://doi.org/10.1186/1471-2202-16-S1-O12
- Computational Model
- Prior Information
- Discrimination Task
- Current Event
- Reading Skill